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In order to take steps towards establishing a method- ology for evaluating Natural Language systems, we conducted a case study. We attempt to evaluate two different approaches to anaphoric processing …...

Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule- based methods. In this paper, we present a sim- …...

An algorithm is proposed to determine an- tecedents for VP ellipsis. The algorithm elim- inates impossible antecedents, and then im- poses a preference ordering on possible an- tecedents. The algorithm …...

This paper describes Picky, a probabilistic agenda-based chart parsing algorithm which uses a technique called p~'ob- abilistic prediction to predict which grammar rules are likely to lead to an acceptable …...

We describe a generative probabilistic model of natural lan- guage, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorpo- rates lexical, syntactic, semantic, …...

Previous work [Gale, Church and Yarowsky, 1992] showed that with high probability a polysemous word has one sense per discourse. In this paper we show that for certain definitions of …...

This paper presents a method for inducing the parts of speech of a language and part- of-speech labels for individual words from a large text corpus. Vector representations for the …...

We describe a mechanism for automatically acquiring verb subcategorization frames and their frequencies in a large corpus. A tagged corpus is first partially parsed to identify noun phrases and then …...

This paper describes a "bootstrapping" method which uses a broad-coverage, rule-based parser to compute probabilities while parsing an untagged corpus of NL text, and which then incorporates those probabilities into …...

This paper presents a statistical decision procedure for lexical ambiguity resolution. The algorithm exploits both local syntactic patterns and more distant collo- cational evidence, generating an efficient, effective, and highly …...

We describe an efficient bottom-up parser that in- terleaves syntactic and semantic structure build- ing. Two techniques are presented for reducing search by reducing local ambiguity: Limited left- context constraints …...

Many documents are available to a computer only as images from paper. However, most nat- ural language processing systems expect their input as character-coded text, which may be difficult or …...

We present a new approach to disambiguating syn- tactically ambiguous words in context, based on Variable Memory Markov (VMM) models. In con- trast to fixed-length Markov models, which predict based …...

The authors propose a model for analyz- ing English sentences including coordinate conjunctions such as "and", "or", "but" and the equivalent words. Syntactic analysis of the English coordinate sentences is …...

Collocations are notoriously difficult for non-native speakers to translate, primarily because they are opaque and can not be translated on a word by word basis. We describe a program named …...

Recent work has considered corpus-based or statistical approaches to the problem of prepositional phrase attachment ambiguity. Typically, ambiguous verb phrases of the form v rip1 p rip2 are resolved through …...

Syntactic natural language parsers have shown themselves to be inadequate for pro- cessing highly-ambiguous large-vocabulary text, as is evidenced by their poor per- formance on domains like the Wall Street …...

This paper presents an unsupervised learn- ing algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations. The …...

This paper snggests a method to align Korean-English parallel corpus. '1?he structural dissimilarity between Korean and Indo-European languages requires more flexible measures to evaluate the alignment candidates between the bilin- …...

In this paper, we present a new approach for word sense disambiguation (WSD) us- ing an exemplar-based learning algorithm. This approach integrates a diverse set of knowledge sources to disambiguate …...

This paper describes a prototype disam- biguation module, KANKEI, which was tested on two corpora of the TRAINS project. In ambiguous verb phrases of form V ... NP PP or …...

We compare the effectiveness of two related • machine translation models applied to the same limited-domain task. One is a trans- fer model with monolingual head automata for analysis and …...

This paper presents a method to combine a set of unsupervised algorithms that can accurately disambiguate word senses in a large, completely untagged corpus. Al- though most of the techniques …...

We describe here an algorithm for detect- ing subject boundaries within text based on a statistical lexical similarity measure. Hearst has already tackled this problem with good results (Hearst, 1994). …...

We identify and validate from a large cor- pus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints …...

In this paper we present the results of the combination of stochastic and rule-based disambiguation methods applied to Basque languagel. The methods we have used in disambiguation are Constraint Grammar …...

In this paper we present the results of the combination of stochastic and rule-based disambiguation methods applied to Basque languagel. The methods we have used in disambiguation are Constraint Grammar …...

We describe two systems: GATE (General Ar- chitecture for Text Engineering), an architec- ture to aid in the production and delivery of language engineering systems which signifi- cantly reduces development …...

We show how the DOP model can be used for fast and robust processing of spoken input in a practical spoken dialogue system called OVIS. OVIS, Openbaar Vervoer Informatie Systeem …...

We show how the DOP model can be used for fast and robust processing of spoken input in a practical spoken dialogue system called OVIS. OVIS, Openbaar Vervoer Informatie Systeem …...

In this paper we present an approach to the dis- ambiguation of capitalized words when they are used in the positions where capitalization is ex- pected, such as the first …...

This paper examines the use of an unsuper- vised statistical model for determining the at- tachment of ambiguous coordinate phrases (CP) of the form nl p n2 cc n3. The …...

In this paper, we present a learning approach for coreference resolution of noun phrases in unrestricted text. The approach learns from a small, annotated corpus and the task in- cludes …...

This paper explores the automatic construction of a multilingual Lexical Knowledge Base from pre-existing lexical resources. We present a new and robust approach for linking already existing lexical/semantic hierarchies. We …...

In this paper we use various methods for multiple neural network combination in tasks of prepo- sitional phrase attachment. Experiments with aggregation functions such as unweighted and weighted average, OWA …...

This paper proposes a new unsupervised learning method for obtaining English part-of- speech(POS) disambiguation rules which would improve the accuracy of a POS tagger. This method has been implemented in …...

Compound noun analysis is one of the crucial prob- lems in Korean language processing because a series of nouns in Korean may appear without white space in real texts, which …...

Word Sense Disambiguation (WSD) is a central task in the area of Natural Language Processing. In the past few years several context-based probabilistic and machine learning methods for WSD have …...

The bigram language models are popular, in much language processing applications, in both Indo-European and Asian languages. However, when the language model for Chinese is applied in a novel domain, …...

Long sentence analysis has been a critical problem because of high complexity. This pa- per addresses the reduction of parsing com- plexity by intra-sentence segmentation, and presents maximum entropy model …...

In this paper, we present a solution to the prob- lem of generating Japanese numeral classifiers us- ing semantic classes from an ontology. Most nouns must take a numeral classifier …...

We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization perfor- mance even with input data of high dimensional feature spaces. …...

In a language generation system, a content planner embodies one or more “plans” that are usually hand–crafted, sometimes through manual analysis of target text. In this paper, we present a …...

This paper proposes a three-tier prosodic hierarchy, including prosodic word, intermediate phrase and intonational phrase tiers, for Mandarin that emphasizes the use of the prosodic word instead of the lexical …...

AbstractWe describe the automatic resolution of pronominal anaphora using KANT Controlled English (KCE) and the KANTOO English-to-Spanish MT system. Our algorithm is based on a robust, syntax-based approach that applies …...

This paper describes two distinct attempts at the SENSEVAL-2 Japanese translation task. The first im- plementation is based on lexical similarity and builds on the results of Baldwin (2001b; 2001a), …...

We propose an algorithm for the automatic acquisition of a bilingual lexicon in the legal domain. We make use of a parallel corpus of bilingual court judgments, aligned to the …...

This paper presents an unsupervised method for assembling semantic knowledge from a part-of- speech tagged corpus using graph algorithms. The graph model is built by linking pairs of words which …...

We describe the architecture of the AskMSR question answering system and systematically evaluate contributions of different system components to accuracy. The system differs from most question answering systems in its …...

In this paper, we evaluate a vari- ety of knowledge sources and super- vised learning algorithms for word sense disambiguation on SENSEVAL-2 and SENSEVAL-1 data. Our knowledge sources include the …...

We explore how active learning with Sup- port Vector Machines works well for a non-trivial task in natural language pro- cessing. We use Japanese word segmenta- tion as a test …...

We consider here the problem of Base Noun Phrase translation. We propose a new method to perform the task. For a given Base NP, we first search its translation candidates …...

Covering ambiguity is one of the two basic types of ambiguities in Chinese word segmentation. We regard its resolution as equivalent to word sense disambiguation, and make use of the …...

This paper proposes a method of speech inten- tion understanding based on dialogue examples. The method uses a spoken dialogue corpus with intention tags to regard the intention of each …...

Extracting sentences that contain important in- formation from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar to those …...

We describe an LR parser of parts-of- speech (and punctuation labels) for Tree Adjoining Grammars (TAGs), that solves table conflicts in a greedy way, with lim- ited amount of backtracking. …...

Ambiguity is very high for location names. For example, there are 23 cities named ‘Buffalo’ in the U.S. Country names such as ‘Canada’, ‘Brazil’ and ‘China’ are also city names …...

Context is used in many NLP systems as an indicator of a term’s syntactic and se- mantic function. The accuracy of the sys- tem is dependent on the quality and …...

Text normalization is an important aspect of successful information retrieval from medical documents such as clinical notes, radiology reports and discharge summaries. In the medical domain, a significant part of …...

This paper presents the strategy and design of a highly efficient semiautomatic method for labelling the semantic features of common nouns, using semantic relationships between words, and based on the …...

This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not rec- ommended (thumbs down). The classifi- cation of a review is predicted by …...

Word sense is ambiguous in natural language processing (NLP). This phenomenon is particularly keen in cases involving noun-verb (NV) word-pairs. This paper describes a sense-based noun-verb event frame (NVEF) identifier …...

Supertagging is the tagging process of assigning the correct elementary tree of LTAG, or the correct supertag, to each word of an input sentence1. In this pa- per we propose …...

Currently, the most common technique for Natural Language parsing is done by using pattern matching through references to a database with the aid of grammatical structures models. But the huge …...

In this paper, we present a learning ap- proach to the scenario template task of information extraction, where information filling one template could come from mul- tiple sentences. When tested …...

A central problem of word sense disam- biguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an ap- proach to automatically …...

Kernel-based learning (e.g., Support Vec- tor Machines) has been successfully ap- plied to many hard problems in Natural Language Processing (NLP). In NLP, al- though feature combinations are crucial to …...

This paper reports on experiments in clas- sifying the semantic role annotations as- signed to prepositional phrases in both the PENN TREEBANK and FRAMENET. In both cases, experiments are done …...

Topic segmentation, which aims to fmd the boundaries between topic blocks in a text, is an important task for semantic analysis of texts. Although different solutions have been proposed for …...

This paper describes an unsupervised algo- rithm for placing unknown words into a taxon- omy and evaluates its accuracy on a large and varied sample of words. The algorithm works …...

In Chinese, anaphors are frequently omitted, termed zero anaphor (ZA), from text due to their prominence. Thus the information carried by ZAs in text can not be used to contribute …...

We present a geometric view on bilingual lexicon extraction from comparable corpora, which allows to re-interpret the methods proposed so far and iden- tify unresolved problems. This motivates three new …...

Given a collection of discrete random variables representing outcomes of learned local predic- tors in natural language, e.g., named entities and relations, we seek an optimal global as- signment to …...

This paper applies machine learning techniques to acquiring aspects of the meaning of discourse mark- ers. Three subtasks of acquiring the meaning of a discourse marker are considered: learning its …...

In this paper we investigate whether paragraphs can be identifi ed automatically in different languages and domains. We propose a machine learning ap- proach which exploits textual and discourse cues …...

The success of supervised learning approaches to word sense disambiguation is largely de- pendent on the features used to represent the context in which an ambiguous word occurs. Previous work …...

. In this paper, a Mandarin speech based emotion classification method is presented. Five primary human emotions including anger, boredom, happiness, neutral and sadness are investigated. For speech emotion recognition, …...

Word Sense Disambiguation (WSD) is the task of choosing the right sense of an ambiguous word given a context. Using Naive Bayesian (NB) classifiers is known as one of the …...

We describe a statistical approach for modeling agreements and disagreements in conversational in- teraction. Our approach first identifies adjacency pairs using maximum entropy ranking based on a set of lexical, …...

In this paper we propose a data intensive ap- proach for inferring sentence-internal tempo- ral relations, which relies on a simple prob- abilistic model and assumes no manual cod- ing. …...

The morphology of Semitic languages is unique in the sense that the major word-formation mechanism is an inherently non-concatenative process of inter- digitation, whereby two morphemes, a root and a …...

We present a novel algorithm for Japanese dependency analysis. The algorithm allows us to analyze dependency structures of a sentence in linear-time while keeping a state-of-the-art accuracy. In this paper, …...

In this paper we describe a way to discover Named Entities by using the distribution of words in news articles. Named Entity recog- nition is an important task for today’s …...

This paper presents a new open text word sense disambiguation method that combines the use of logical inferences with PageRank-style algo- rithms applied on graphs extracted from natu- ral language …...

There are a lot of differences between expres- sions used in written language and spoken lan- guage. It is one of the reasons why speech syn- thesis applications are prone …...

We present a new HMM tagger that exploits context on both sides of a word to be tagged, and evaluate it in both the unsupervised and supervised case. Along the …...

This paper describes the role of supertagging in a wide-coverage CCG parser which uses a log-linear model to select an analysis. The supertagger reduces the derivation space over which model …...

. How can recent advances in automating the evaluation of machine translation (MT) engines be applied to automate the evaluation of more complex embedded MT systems? In this paper, we …...

Although vast amounts of textual data are freely available, many NLP algorithms exploit only a minute percentage of it. In this paper, we study the challenges of working at the …...

Empirical experience and observations have shown us when powerful and highly tunable classifiers such as maximum en- tropy classifiers, boosting and SVMs are applied to language processing tasks, it is …...

. Temporal question classification assigns time granularities to tempo- ral questions ac-cording to their anticipated answers. It is very important for an- swer extraction and verification in the literature of …...

In this work, we provide an empiri- cal analysis of differences in word use between genders in telephone conversa- tions, which complements the consid- erable body of work in sociolinguistics …...

. Conventional QA systems cannot answer to the questions composed of two or more sentences. Therefore, we aim to construct a QA system that can answer such multiple-sentence questions. As …...

Previous research applying kernel meth- ods to natural language parsing have fo- cussed on proposing kernels over parse trees, which are hand-crafted based on do- main knowledge and computational con- …...

This paper investigates automatic identi- fication of Information Structure (IS) in texts. The experiments use the Prague Dependency Treebank which is annotated with IS following the Praguian approach of Topic …...

. This paper proposes a method for detecting errors concern- ing article usage and singular/plural usage based on the mass count distinction. Although the mass count distinction is particularly impor- …...

We propose a method for extracting se- mantic orientations of words: desirable or undesirable. Regarding semantic ori- entations as spins of electrons, we use the mean field approximation to compute …...

. Building a thesaurus is very costly and time-consuming task. To alleviate this problem, this paper proposes a new method for extending a thesaurus by adding taxonomic information automatically extracted …...

Language identification has been an interesting and fascinating issue in natural language processing for decades, and there have been many researches on it. However, most of the researches are for …...

This paper considers the problem of auto- matic assessment of local coherence. We present a novel entity-based representa- tion of discourse which is inspired by Cen- tering Theory and can …...

We formalize weighted dependency pars- ing as searching for maximum spanning trees (MSTs) in directed graphs. Using this representation, the parsing algorithm of Eisner (1996) is sufficient for search- ing …...

We use logical inference techniques for recognising textual entailment. As the performance of theorem proving turns out to be highly dependent on not read- ily available background knowledge, we incorporate …...

. This paper shows that our WSD system using rich linguistic features achieved high accuracy in the classification of English SENSEVAL2 verbs for both fine-grained (64.6%) and coarse-grained (73.7%) senses. …...

The applicability of many current information ex- traction techniques is severely limited by the need for supervised training data. We demonstrate that for certain field structured extraction tasks, such as …...

. We explore the use of a partially annotated corpus to build a depen- dency parser for Japanese. We examine two types of partially annotated corpora. It is found that …...

We investigate the unsupervised detection of semi-fixed cue phrases such as “This paper proposes a novel approach. . . 1” from unseen text, on the basis of only a handful …...

This paper shows that inference rules with temporal constraints can be acquired by us- ing verb-verb co-occurrences in Japanese coordinated sentences and verb-noun co- occurrences. For example, our unsuper- vised …...

This paper presents a method of automat- ically constructing information extraction patterns on predicate-argument structures (PASs) obtained by full parsing from a smaller training corpus. Because PASs represent generalized structures …...

. Multiple target translations are due to several meanings of source words, and various target word equivalents depending on the context of the source word. Thus, an automated approach is …...

The driving vision for our work is to provide intelligent, automated assistance to users in understanding the status of their email conversations. Our approach is to create tools that enable …...

This paper describes an extremely lexi- calized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are de- fined with only the probabilities …...

We consider the problem of constructing a directed acyclic graph that encodes tem- poral relations found in a text. The unit of our analysis is a temporal segment, a frag- …...

In this paper we address the issue of au- tomatically assigning information status to discourse entities. Using an annotated cor- pus of conversational English and exploit- ing morpho-syntactic and lexical …...

In this paper, we present a rule based model for morphological disambiguation of Turkish. The rules are generated by a novel decision list learning algorithm us- ing supervised training. Morphological …...

Work on the semantics of questions has argued that the relation between a ques- tion and its answer(s) can be cast in terms of logical entailment. In this paper, we …...

We propose a supervised, two-phase framework to address the problem of para- phrase recognition (PR). Unlike most PR systems that focus on sentence similarity, our framework detects dissimilarities be- tween …...

This paper studies the impact of para- phrases on the accuracy of automatic eval- uation. Given a reference sentence and a machine-generated sentence, we seek to find a paraphrase of …...

. This paper introduced a semantic parsing model constructed above a symbolic system of concepts for understanding natural language. Based on the model a sentence can be mapped into the …...

This study aims at identifying when an event written in text occurs. In particular, we classify a sentence for an event into four time-slots; morning, daytime, eve- ning, and night. …...

Aligning sentences belonging to compa- rable monolingual corpora has been sug- gested as a first step towards training text rewriting algorithms, for tasks such as summarization or paraphrasing. We present …...

While it is generally agreed that Word Sense Disambiguation (WSD) is an application-dependent task, the great majority of systems pursue application-independent approaches. We propose a strategy to support WSD for …...

For the Affective Text task at Semeval- 1/Senseval-4, the CLaC team compared a knowledge-based, domain-independent ap- proach and a standard, statistical machine learning approach to ternary sentiment an- notation of …...

In this paper, we present an election predic- tion system (Crystal) based on web users’ opinions posted on an election prediction website. Given a prediction message, Crys- tal first identifies …...

When a word sense disambiguation (WSD) system is trained on one domain but ap- plied to a different domain, a drop in ac- curacy is frequently observed. This high- lights …...

In this paper, we address a unique problem in Chinese language processing and report on our study on extending a Chinese the- saurus with region-specific words, mostly from the financial …...

We describe a novel neural network archi- tecture for the problem of semantic role la- beling. Many current solutions are compli- cated, consist of several stages and hand- built features, …...

For the metonymy resolution task SemEval-2007, the use of a memory-basedat learner to train classifiers for the identifica- tion of metonymic location names is inves- tigated. Metonymy is resolved on …...

We propose a novel method for Japanese de- pendency analysis, which is usually reduced to the construction of a dependency tree. In deterministic approaches to this task, depen- dency trees …...

We present a novel approach to the word sense disambiguation problem which makes use of corpus-based evidence com- bined with background knowledge. Em- ploying an inductive logic programming algorithm, the …...

This paper presents a novel application of Alternating Structure Optimization (ASO) to the task of Semantic Role Labeling (SRL) of noun predicates in NomBank. ASO is a recently proposed linear …...

We present in this paper methods to improve HMM-based part-of-speech (POS) tagging of Mandarin. We model the emission prob- ability of an unknown word using all the characters in the …...

This paper assesses the role of multi-label classification in modelling polysemy for lan- guage acquisition tasks. We focus on the ac- quisition of semantic classes for Catalan ad- jectives, and …...

Morphological analysis and disambiguation are crucial stages in a variety of natural language processing applications, especially when languages with complex morphology are concerned. We present a system which disambiguates the …...

. In this paper, we propose a method to classify movie review documents into positive or negative opinions. There are several approaches to classify documents. The previous studies, however, used …...

This paper examines whether a learning- based coreference resolver can be improved using semantic class knowledge that is au- tomatically acquired from a version of the Penn Treebank in which …...

This paper provides an algorithmic frame- work for learning statistical models involv- ing directed spanning trees, or equivalently non-projective dependency structures. We show how partition functions and marginals for directed …...

This paper describes a supervised, knowledge-intensive approach to the auto- matic identification of semantic relations between nominals in English sentences. The system employs different sets of new and previously used …...

This short paper presents a system developed at the Université Paris 13 for the Semeval 2007 Metonymy Resolution Task (task #08, location name track; see Markert and Nissim, 2007). The …...

For the Affective Text task at SemEval- 2007, University Paris 7’s system first evaluates emotion and valence on all words of a news headline (using enriched versions of SentiWordNet and …...

We describe two systems participating of the English Lexical Sample task in SemEval- 2007. The systems make use of Inductive Logic Programming for supervised learning in two different ways: (a) …...

This paper investigates why the HMMs es- timated by Expectation-Maximization (EM) produce such poor results as Part-of-Speech (POS) taggers. We find that the HMMs es- timated by EM generally assign …...

Online reviews are often accompanied with numerical ratings provided by users for a set of service or product aspects. We propose a statistical model which is able to discover corresponding …...

In this paper, we take Determinative-Measure Compounds as an example to demonstrate how the E-HowNet semantic composition mechanism works in deriving the sense representations for all determinative-measure (DM) compounds which …...

VerbNet (VN) is a major large-scale En- glish verb lexicon. Mapping verb instances to their VN classes has been proven use- ful for several NLP tasks. However, verbs are polysemous …...

Graph-based and transition-based approaches to dependency parsing adopt very different views of the problem, each view having its own strengths and limitations. We study both approaches under the framework of …...

AbstractSome time in the future, some spelling error correction system will correct all the errors, and only the errors. We need evaluation metrics that will tell us when this has …...

Most attempts to integrate FrameNet in NLP systems have so far failed because of its lim- ited coverage. In this paper, we investigate the applicability of distributional and WordNet- based …...

Some phrases can be interpreted either id- iomatically (figuratively) or literally in con- text, and the precise identification of idioms is indispensable for full-fledged natural lan- guage processing (NLP). To …...

Most research related to unithood were con- ducted as part of a larger effort for the deter- mination of termhood. Consequently, nov- elties are rare in this small sub-field of …...

This paper describes the two algorithms we developed for the CoNLL 2008 Shared Task “Joint learning of syntactic and se- mantic dependencies”. Both algorithms start parsing the sentence using the …...

In this paper we present our syntactic and semantic dependency parsing system par- ticipated in both closed and open compe- titions of the CoNLL 2008 Shared Task. By combining the …...

We propose using large-scale clustering of de- pendency relations between verbs and multi- word nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since depen- dency relations capture …...

Previous work on ordering events in text has typically focused on local pairwise decisions, ignoring globally inconsistent labels. How- ever, temporal ordering is the type of domain in which global …...

Paraphrases have proved to be useful in many applications, including Machine Translation, Question Answering, Summarization, and In- formation Retrieval. Paraphrase acquisition methods that use a single monolingual corpus often produce …...

This work describes an answer ranking engine for non-factoid questions built using a large online community-generated question-answer collection (Yahoo! Answers). We show how such collections may be used to effectively …...

Determining the polarity of a sentiment- bearing expression requires more than a sim- ple bag-of-words approach. In particular, words or constituents within the expression can interact with each other to …...

In this paper, we first introduce a new archi- tecture for parsing, bidirectional incremental parsing. We propose a novel algorithm for in- cremental construction, which can be applied to many …...

Name origin recognition is to identify the source language of a personal or location name. Some early work used either rule- based or statistical methods with single knowledge source. In …...

This paper proposes an other-anaphora resolution approach in bio-medical texts. It utilizes automatically mined patterns to discover the semantic relation between an anaphor and a candidate antecedent. The knowledge from …...

Question classification plays an important role in question answering. Features are the key to obtain an accurate question classifier. In con- trast to Li and Roth (2002)’s approach which makes …...

This paper describes a computational ap- proach to resolving the true referent of a named mention of a person in the body of an email. A generative model of mention …...

In this paper, we study the problem of sum- marizing email conversations. We first build a sentence quotation graph that captures the conversation structure among emails. We adopt three cohesion …...

This paper presents a comparative evalua- tion of several state-of-the-art English parsers based on different frameworks. Our approach is to measure the impact of each parser when it is used …...

Addressing the task of acquiring semantic relations between events from a large cor- pus, we first argue the complementarity be- tween the pattern-based relation-oriented approach and the anchor-based argument- oriented …...

In this paper we present a study on the interpretation of weekday names in texts. Our algorithm for assigning a date to a weekday name achieves 95.91% accuracy on a …...

This study presents a novel approach to the problem of system portability across differ- ent domains: a sentiment annotation system that integrates a corpus-based classifier trained on a small set …...

Information Extraction, from the electronic clinical record is a comparatively new topic for computational linguists. In order to utilize the records to improve the efficiency and quality of health care, …...

Financial investors trade on the basis of infor- mation, and in particular, on the likelihood that a piece of information will impact the mar- ket. The ability to predict this …...

Jointly parsing two languages has been shown to improve accuracies on either or both sides. However, its search space is much bigger than the monolingual case, forcing existing approaches to …...

. This paper investigates how to best couple hand-annotated data with information extracted from an external lexical resource to improve POS tagging performance. Focusing on French tagging, we introduce a …...

Mitchell et al. (2008) demonstrated that corpus-extracted models of semantic knowledge can predict neural activation patterns recorded using fMRI. This could be a very powerful technique for evaluating conceptual models …...

Generic relation identification (GRI) aims to build models of relation-forming entity pairs that can be transferred across domains without modification of model parameters. GRI has high utility in terms of …...

Automatically extracting social meaning and intention from spoken dialogue is an impor- tant task for dialogue systems and social com- puting. We describe a system for detecting elements of interactional …...

Parsers are often the bottleneck for data ac- quisition, processing text too slowly to be widely applied. One way to improve the efficiency of parsers is to construct more confident …...

This paper presents a simple and effective approach to improve dependency parsing by using subtrees from auto-parsed data. First, we use a baseline parser to parse large-scale unannotated data. Then …...

Automatically detecting human social in- tentions from spoken conversation is an important task for dialogue understand- ing. Since the social intentions of the speaker may differ from what is perceived …...

We propose a unified approach to web search query alterations in Japanese that is not lim- ited to particular character types or ortho- graphic similarity between a query and its …...

We present a language-pair independent terminology extraction module that is based on a sub-sentential alignment sys- tem that links linguistically motivated phrases in parallel texts. Statistical filters are applied on …...

The paper presents the results of a project com- pleted by the authors for realizing a contin- uous speech recognition system for Bulgarian. The state-of-the-art speech recognition technol- ogy used …...

This paper describes a method using mor- phological rules and heuristics, for the au- tomatic extraction of large-coverage lexi- cons of stems and root word-forms from a raw text corpus. …...

We present a method for performing machine transliteration without any parallel resources. We frame the transliteration task as a deci- pherment problem and show that it is possi- ble to …...

In this paper we address the problem of identifying reciprocal relationships in English. In particular we introduce an algorithm that semi-automatically discovers patterns encod- ing reciprocity based on a set …...

In this paper, we describe experiments con- ducted on identifying a person using a novel unique correlated corpus of text and audio samples of the person’s communication in six genres. …...

This paper proposes a method that speeds up a classifier trained with many con- junctive features: combinations of (prim- itive) features. The key idea is to pre- compute as partial …...

We report in this paper a way of doing Word Sense Disambiguation (WSD) that has its ori- gin in multilingual MT and that is cognizant of the fact that parallel …...

Automatic detection of general relations between short texts is a complex task that cannot be carried out only relying on lan- guage models and bag-of-words. There- fore, learning methods to …...

. Part of Speech (POS) tagging is the task of labeling each word in a sentence with its appropriate syntactic category called part of speech. POS tagging is a very …...

. In this paper, we introduce a minimally supervised method for learning to classify named-entity titles in a given encyclopedia into broad semantic categories in an existing ontology. Our main …...

We define a probabilistic morphological ana- lyzer using a data-driven approach for Syriac in order to facilitate the creation of an annotated corpus. Syriac is an under-resourced Semitic language for …...

Several recent discourse parsers have em- ployed fully-supervised machine learning ap- proaches. These methods require human an- notators to beforehand create an extensive training corpus, which is a time-consuming and …...

Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated feature weighting schemes from Information …...

AbstractThis paper presents the ADN-Classifier, an Automatic classification system of Spanish Deverbal Nominalizations aimed at identifying its semantic denotation (i.e. event, result, underspecified, or lexicalized). The classifier can be used …...

This paper proposes a fast and simple unsuper- vised word segmentation algorithm that uti- lizes the local predictability of adjacent char- acter sequences, while searching for a least- effort representation …...

AbstractIn this work we propose a hybrid unsupervised approach for semantic relation extraction from Italian and English texts. The system takes as input pairs of ""distributionally similar"" terms, possibly involved …...

AbstractThe Arabic language has a very rich morphology where a word is composed of zero or more prefixes, a stem and zero or more suffixes. This makes Arabic data sparse …...

: The aim of this study is to build natural language resources for languages with limited resources or minority languages. Manually building these resources is tedious and costly. These natural …...

There is significant evidence in the literature that integrating knowledge about multiword expressions can improve shallow parsing ac- curacy. We present an experimental study to quantify this improvement, focusing on …...

We present Quantized Contour Modeling (QCM), a Bayesian approach to the classification of acoustic contours. We evaluate the performance of this tech- nique in the classification of prosodic events. We …...

Written contracts are a fundamental framework for commercial and coopera- tive transactions and relationships. Lim- ited research has been published on the ap- plication of machine learning and natural language …...

AbstractThis paper first describes an experiment to construct an English-Chinese parallel corpus, then applying the Uplug word alignment tool on the corpus and finally produce and evaluate an English-Chinese word …...

In this paper, we systematically assess the value of using web-scale N-gram data in state-of-the-art supervised NLP classifiers. We compare classifiers that include or ex- clude features for the counts …...

Automatically finding email messages that contain requests for action can provide valu- able assistance to users who otherwise strug- gle to give appropriate attention to the ac- tionable tasks in …...

. Some users abuse the anonymity and disrupt communications in a community site. Authorship identification based on analyzing stylistic features of messages is effective in detecting these inadequate users. However, …...

This paper addresses the problem of learning phrase patterns for unsupervised speaker role classification. Phrase patterns are automati- cally extracted from large corpora, and redun- dant patterns are removed via …...

. This paper describes the work on automated Information Extraction that accepts arbitrary text and extracts information from the text. A new approach to implement Information Extraction system is proposed …...

This paper proposes an approach to ref- erence resolution in situated dialogues by exploiting extra-linguistic information. Recently, investigations of referential be- haviours involved in situations in the real world have …...

Temporal information extraction is a popular and interesting research field in the area of Natural Language Processing (NLP). In this paper, we report our works on TempEval-2 shared task. This …...

A challenging problem in open informa- tion extraction and text mining is the learn- ing of the selectional restrictions of se- mantic relations. We propose a mini- mally supervised bootstrapping …...

This paper address the problem of entity link- ing. Specifically, given an entity mentioned in unstructured texts, the task is to link this entity with an entry stored in the …...

AbstractThe paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model …...

In this paper we consider the problem of building a system to predict readability of natural-language documents. Our sys- tem is trained using diverse features based on syntax and language …...

Constrained decoding is of great importance not only for speed but also for translation qual- ity. Previous efforts explore soft syntactic con- straints which are based on constituent bound- aries …...

This paper examines tagging models for spon- taneous English speech transcripts. We ana- lyze the performance of state-of-the-art tag- ging models, either generative or discrimi- native, left-to-right or bidirectional, with …...

AbstractIn the POS tagging task, there are two kinds of statistical models: one is generative model, such as the HMM, the others are discriminative models, such as the Maximum Entropy …...

In many applications, replacing a complex word form by its stem can reduce sparsity, re- vealing connections in the data that would not otherwise be apparent. In this paper, we …...

The main task we address in our research is classification of text using fine-grained attitude labels. The developed @AM sys- tem relies on the compositionality prin- ciple and a novel …...

. This paper investigates the developmental process through which L2 learners acquire two „imperfective‟ aspect markers in Korean, -ko iss- (progressive and resultative) and -a iss- (resultative) which attempts to …...

AbstractIn this paper, we present a morphosyntactic tagset for Afrikaans based on the guidelines developed by the Expert Advisory Group on Language Engineering Standards (EAGLES). We compare our slim yet …...

In addition to a high accuracy, short pars- ing and training times are the most impor- tant properties of a parser. However, pars- ing and training times are still relatively …...

This paper proposes a novel approach to the problem of training classifiers to detect and correct grammar and usage errors in text by selectively introducing mistakes into the train- ing …...

It is well known that parsing accuracies drop significantly on out-of-domain data. What is less known is that some parsers suffer more from domain shifts than others. We show that …...

We investigate active learning methods for Japanese dependency parsing. We propose active learning methods of using partial dependency relations in a given sentence for parsing and evaluate their effective- ness …...

Unknown words are a hindrance to the perfor- mance of hand-crafted computational gram- mars of natural language. However, words with incomplete and incorrect lexical entries pose an even bigger problem …...

We show that Viterbi (or “hard”) EM is well-suited to unsupervised grammar in- duction. It is more accurate than standard inside-outside re-estimation (classic EM), significantly faster, and simpler. Our ex- …...

This paper proposes a new method for ap- proximate string search, specifically candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system …...

Argumentative Zoning (AZ) – analysis of the argumentative structure of a scientific paper – has proved useful for a number of informa- tion access tasks. Current approaches to AZ rely …...

This paper describes a supervised algorithm for diacritic restoration based on naive Bayes classifiers that act at word- level. Classifications are based on a rich set of features, extracted automatically …...

We investigate whether wording, stylistic choices, and online behavior can be used to predict the age category of blog authors. Our hypothesis is that significant changes in writing style distinguish …...

The ALTA shared tasks are programming competitions where all participants attempt to solve the same problem, and the winner is the system with the best results. The 2011 ALTA shared …...

This paper discusses two Hidden Markov Models (HMM) for linking linguistically motivated XTAG grammar and the auto- matically extracted LTAG used by MICA parser. The former grammar is a detailed …...

Attempts to profile authors according to their characteristics extracted from textual data, in- cluding native language, have drawn attention in recent years, via various machine learn- ing approaches utilising mostly …...

Most previous work on multilingual sentiment analysis has focused on methods to adapt sentiment resources from resource-rich languages to resource-poor languages. We present a novel approach for joint bilingual sentiment …...

Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured data to heuristically label a training corpus, …...

Cross-document coreference, the task of grouping all the mentions of each entity in a document collection, arises in information ex- traction and automated knowledge base con- struction. For large collections, …...

Traditional text similarity measures consider each term similar only to itself and do not model semantic relatedness of terms. We pro- pose a novel discriminative training method that projects the …...

The fuzziness of Chinese sentence boundary makes discourse analysis more challenging. Moreover, many articles posted on the Internet are even lack of punctuation marks. In this pa- per, we collect …...

Disambiguating named entities in natural- language text maps mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base such as DBpedia or YAGO. This …...

CCGs are directly compatible with binary- branching bottom-up parsing algorithms, in particular CKY and shift-reduce algorithms. While the chart-based approach has been the dominant approach for CCG, the shift-reduce method …...

This paper addresses a data-driven surface realisation model based on a large-scale re- versible grammar of German. We investigate the relationship between the surface realisa- tion performance and the character …...

This paper explores the use of bilingual par- allel corpora as a source of lexical knowl- edge for cross-lingual textual entailment. We claim that, in spite of the inherent difficul- …...

Resolving coordination ambiguity is a clas- sic hard problem. This paper looks at co- ordination disambiguation in complex noun phrases (NPs). Parsers trained on the Penn Treebank are reporting impressive …...

In this paper, we introduce a knowledge-based method to disambiguate biomedical acronyms using second-order co-occurrence vectors. We create these vectors using information about a long-form obtained from the Unified Medical …...

AbstractIn this paper, we investigate the usage of a non-canonical German passive alternation for ditransitive verbs, the recipient passive, in naturally occuring corpus data. We propose a classifier that predicts …...

Started from the very beginning, Stemming has been playing significant roles in several Natural Language Processing Applications such as information retrieval (IR), machine translation (MT), morph analysis and deciding the …...

Most current dependency parsers presuppose that input words have been morphologically disambiguated using a part-of-speech tagger before parsing begins. We present a transition- based system for joint part-of-speech tagging and …...

Bilingual lexicon construction (BLC) from comparable corpora is based on the idea that bilingual similar words tend to occur in similar contexts, usually of words. This, however, introduces noise and …...

AbstractFinding useful questions is a challenging task in Community Question Answering (CQA). There are two key issues need to be resolved: 1) what is a useful question to the given …...

We present a classifier that discriminates be- tween types of corrections made by teachers of English in student essays. We define a set of linguistically motivated feature templates for a …...

AbstractTypically, accuracy is used to represent the performance of an NLP system. However, accuracy attainment is a function of investment in annotation. Typically, the more the amount and sophistication of …...

It has been established that incorporating word cluster features derived from large unlabeled corpora can significantly improve prediction of linguistic structure. While previous work has focused primarily on English, we …...

The usual challenges of transcribing spoken language are compounded for Southern Min (Taiwanese) because it lacks a generally accepted orthography. This study reports the development and testing of software tools …...

In this paper, we revisit the problem of language identification with the focus on proper discrimination between closely related languages. Strong similarities between certain languages make it very hard to …...

We propose a new method for entity set expan- sion that achieves highly accurate extraction by suppressing the effect of semantic drift; it requires a small amount of interactive infor- …...

The possibility of deleting a word from a sen- tence without violating its syntactic correct- ness belongs to traditionally known manifes- tations of syntactic dependency. We introduce a novel unsupervised …...

We describe a domain-specific method of adapting conditional random fields (CRFs) to mor- phosyntactic tagging of highly-inflectional languages. The solution involves extending CRFs with additional, position-wise restrictions on the output …...

This study aims to infer the social nature of conversations from their content automat- ically. To place this work in context, our moti- vation stems from the need to understand …...

AbstractDue to the rapid growth in the volume of biomedical literature, there is an increasing requirement for high-performance semantic search systems, which allow biologists to perform precise searches for events …...

This article presents the experiments car- ried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation …...

We investigate paradigmatic representations of word context in the domain of unsupervised syntactic category acquisition. Paradigmatic representations of word context are based on potential substitutes of a word in contrast …...

We present a system for automatic identification of schizophrenic patients and healthy controls based on narratives the subjects recounted about emotional experiences in their own life. The focus of the …...

In this paper we present work on the task of Native Language Identification (NLI). We present an alternative corpus to the ICLE which has been used in most work up …...

AbstractPOS Taggers typically fail to correctly tag grammatical neologisms: for known words, a tagger will only take known tags into account, and hence discard any possibility that the word is …...

This study presents the development and evaluation of pattern matching refinements (PMRs) to automatic code switching point (CSP) detection. With all PMRs, evaluation showed an accuracy of 94.51%. This is …...

In this paper we report our work on a factoid question answering task that avoids named- entity recognition tool in the answer selection process. We use semantic analogical reason- ing …...

AbstractIn this work we investigated whether there is a relationship between dominant behaviour of dialogue participants and their verbal intelligence. The analysis is based on a corpus containing 56 dialogues …...

AbstractWith our experiment, we show how we can detect and annotate clausal coordinate ellipsis with Constraint Grammar rules. We focus on such an elliptical structure in which there are two …...

Neurosemantics aims to learn the mapping between concepts and the neural activity which they elicit during neuroimaging ex- periments. Different approaches have been used to represent individual concepts, but current …...

In this paper, we investigate a full-fledged supervised machine learning framework for identifying English phrasal verbs in a given context. We concentrate on those that we de- fine as the …...

We present an approach to automatically re- cover hidden attributes of scientific articles, such as whether the author is a native English speaker, whether the author is a male or …...

Transition-based dependency parsers are often forced to make attachment deci- sions at a point when only partial infor- mation about the relevant graph configu- ration is available. In this paper, …...

It is becoming clear that traditional evaluation measures used in Computational Linguistics (including Error Rates, Accuracy, Recall, Precision and F-measure) are of limited value for unbiased evaluation of systems, and …...

Online discussion forums are a valuable means for users to resolve specific information needs, both interactively for the participants and statically for users who search/browse over historical thread data. However, …...

Informal and formal (“T/V”) address in dia- logue is not distinguished overtly in mod- ern English, e.g. by pronoun choice like in many other languages such as French (“tu”/“vous”). Our …...

We report on a pilot experiment to improve the per- formance of an automatic speech recognizer (ASR) by using a single-channel EEG signal to classify the speaker’s mental state as …...

AbstractIn order to construct an annotated diachronic corpus of Japanese, we propose to create a new dictionary for morphological analysis of Early Middle Japanese (Classical Japanese) based on UniDic, a …...

We present a supervised learning approach to cross-lingual textual entailment that explores statistical word alignment models to predict entailment relations between sentences writ- ten in different languages. Our approach is …...

Work on authorship attribution has tradition- ally focused on long texts. In this work, we tackle the question of whether the author of a very short text can be successfully …...

The English ’s possessive construction oc- curs frequently in text and can encode several different semantic relations; how- ever, it has received limited attention from the computational linguistics community. This …...

Many statistical learning problems in NLP call for local model search methods. But accu- racy tends to suffer with current techniques, which often explore either too narrowly or too broadly: …...

Using labeled Twitter training data from SemEval-2013, we train both a subjectivity classifier and a polarity classifier separately, and then combine the two into a single hier- archical classifier. Using …...

Sentence completion is a challenging seman- tic modeling task in which models must choose the most appropriate word from a given set to complete a sentence. Although a variety of …...

This paper presents an approach for detecting promotional content in Wikipedia. By incor- porating stylometric features, including fea- tures based on n-gram and PCFG language models, we demonstrate improved accuracy …...

We report the results of our work on automat- ing the transliteration decision of named en- tities for English to Arabic machine trans- lation. We construct a classification-based framework to …...

Feature computation and exhaustive search have significantly restricted the speed of graph-based dependency parsing. We propose a faster framework of dynamic feature selec- tion, where features are added sequentially as …...

This paper describes the IIRG 1 system en- tered in SemEval-2013, the 7th International Workshop on Semantic Evaluation. We partic- ipated in Task 5 Evaluating Phrasal Semantics. We have adopted …...

AbstractJoint morphological and syntactic analysis has been proposed as a way of improving parsing accuracy for richly inflected languages. Starting from a transition-based model for joint part-of-speech tagging and dependency …...

We introduce a novel method to jointly parse and detect disfluencies in spoken utterances. Our model can use arbitrary features for pars- ing sentences and adapt itself with out-of- domain …...

This paper describes our approach to the SemEval-2013 task on “Sentiment Analysis in Twitter”. We use simple bag-of-words mod- els, a freely available sentiment dictionary auto- matically extended with distributionally …...

Automatic metaphor identification and inter- pretation in text have been traditionally con- sidered as two separate tasks in natural lan- guage processing (NLP) and addressed in- dividually within computational frameworks. …...

Linking name mentions in microblog posts to a knowledge base, namely microblog entity linking, is useful for text mining tasks on mi- croblog. Entity linking in long text has been …...

Annotating linguistic data is often a com- plex, time consuming and expensive en- deavour. Even with strict annotation guidelines, human subjects often deviate in their analyses, each bringing different biases, …...

The many differences between Dialectal Ara- bic and Modern Standard Arabic (MSA) pose a challenge to the majority of Arabic natural language processing tools, which are designed for MSA. In …...

Large databases of facts are prevalent in many applications. Such databases are accurate, but as they broaden their scope they become increasingly incomplete. In contrast to extending such a database, …...

This paper introduces the first pattern-based Persian Temporal Relation Classifier (PTRC) that finds the type of temporal relations between pairs of events in the Persian texts. The proposed system uses …...

Expensive feature engineering based on WordNet senses has been shown be useful for document level sentimentto classification. A plausible reason for such a performance improvement is the reduction in data …...

A precise syntacto-semantic analysis of En- glish requires a large detailed lexicon with the possibility of treating multiple tokens as a sin- gle meaning-bearing unit, a word-with-spaces. However parsing with …...

In this paper we describe the system used to participate in the sub task 5b in the Phrasal Se- mantics challenge (task 5) in SemEval 2013. This sub task consists …...

This paper presents the UNITOR system that participated in the *SEM 2013 shared task on Semantic Textual Similarity (STS). The task is modeled as a Support Vector (SV) regression problem, …...

Human engagement in narrative is partially driven by reasoning about discourse relations between narrative events, and the expectations about what is likely to happen next that results from such reasoning. …...

Topic models can be used in an unsuper- vised domain adaptation for Word Sense Disambiguation (WSD). In the domain adaptation task, three types of topic mod- els are available: (1) …...

The measurement of semantic relatedness between two words is an important met- ric for many natural language processing applications. In this paper, we present a novel approach for measuring semantic …...

This paper explores to what extent lemmati- sation, lexical resources, distributional seman- tics and paraphrases can increase the accuracy of supervised models for dialogue manage- ment. The results suggest that …...

AbstractWe demonstrate a method of improving a seed sentiment lexicon developed on essay data by using a pivot-based paraphrasing system for lexical expansion coupled with sentiment profile enrichment using crowdsourcing. …...

This paper describes a dual-classifier ap- proach to contextual sentiment analysis at the SemEval-2013 Task 2. Contextual analysis of polarity focuses on a word or phrase, rather than the broader …...

This paper offers an approach for governments to harness the information contained in social media in order to make public inspections and disclosure more efficient. As a case study, we …...

AbstractThe knowledge about the relation between events is quite useful for coreference resolution, anaphora resolution, and several NLP applications such as dialogue system. This paper presents a large scale database …...

Text-level discourse parsing remains a challenge. The current state-of-the-art overall accuracy in relation assignment is 55.73%, achieved by Joty et al. (2013). However, their model has a high order of …...

We develop a statistical model of saccadic eye movements during reading of isolated sentences. The model is focused on rep- resenting individual differences between readers and supports the inference of …...

AbstractIn this paper, we describe a release of a sizeable monolingual Urdu corpus automatically tagged with part-of-speech tags. We extend the work of Jawaid and Bojar (2012) who use three …...

AbstractThis paper presents an open source part-of-speech tagger for the Norwegian language. It describes how an existing language processing library (FreeLing) was used to build a new part-of-speech tagger for …...

AbstractWe develop a supersense taxonomy for adjectives, based on that of GermaNet, and apply it to English adjectives in WordNet using human annotation and supervised classification. Results show that accuracy …...

. The process of understanding a document uses both visual, logic and discursive information along with the mutual relationships between those levels. Most approaches studying those relationships were conducted in …...

This paper investigates the problem of automated text aesthetics prediction. The avail- ability of user generated content and ratings, e.g. Flickr, has induced research in aesthet- ics prediction for non-text …...

AbstractBilingual dictionaries are vital in many areas of natural language processing, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. Pivot-based induction …...

Manual analysis and decryption of enci- phered documents is a tedious and error prone work. Often—even after spend- ing large amounts of time on a par- ticular cipher—no decipherment can …...

We describe the system entered by the National Research Council Canada in the SemEval-2014 L2 writing assistant task. Our system relies on a standard Phrase-Based Statistical Machine Transla- tion trained …...

This paper presents the first experiments on identifying implicit discourse relations (i.e., relations lacking an overt discourse connective) in French. Given the little amount of annotated data for this task, …...

We present a novel approach for automatic report generation from time-series data, in the context of student feedback genera- tion. Our proposed methodology treats content selection as a multi-label (ML) …...

Open environments present an attention management challenge for conversational systems. We describe a kiosk system (based on Ravenclaw–Olympus) that uses simple auditory and visual information to interpret human presence and …...

AbstractThis paper presents the design and results of a crowdsourcing experiment on the recognition of Italian event nominals. The aim of the experiment was to assess the feasibility of crowdsourcing …...

Sentiment analysis of short texts such as single sentences and Twitter messages is challenging because of the limited contextual information that they normally contain. Effectively solving this task requires strategies …...

We describe a novel approach to error detection in adjective–noun combinations. We present and release a new dataset of annotated errors where the examples are extracted from learner texts and …...

Although hyperlinks enhance the utility of Wikipedia, embedding them in articles imposes a burden on contributors. To alleviate this burden as well as enrich hyperlinks in Wikipedia articles, we propose …...

AbstractThis paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are real-time dependent. Our approach is based on two types of template matching using …...

In this paper we present our task-based evaluation of query biased summarization for cross-language information retrieval (CLIR) using relevance prediction. We de- scribe our 13 summarization methods each from one …...

AbstractWe present FLORS, a new part-of-speech tagger for domain adaptation. FLORS uses robust representations that work especially well for unknown words and for known words with unseen tags. FLORS is …...

The current paper proposes a novel approach to Spanish zero pronoun resolution in the context of Spanish to Korean Machine Translation (MT). Spanish is one of the well-known 'pro-drop' languages …...

. This paper presents the first experiments on French in automatic identification of implicit discourse relations (i.e. relations that lack an overt connective). Our systems exploit hand-labeled implicit examples, along …...

In this paper we briefly describe our super- vised machine learning approach for dis- order mention detection system that we submitted as part of our participation in the SemEval-2014 Shared …...

The shared task on Aspect based Senti- ment Analysis primarily focuses on mining relevant information from the thousands of online reviews available for a popular product or service. In this …...

AbstractInformation Extraction is an important task in Natural Language Processing, consisting of finding a structured representation for the information expressed in natural language text. Two key steps in information extraction …...

This paper addresses implicit opinions expressed via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor, gfbf events). We incorporate the inferences developed by implicature rules into an …...

We examine the embedding approach to reason new relational facts from a large- scale knowledge graph and a text corpus. We propose a novel method of jointly em- bedding entities …...

This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 - Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the …...

This paper presents a novel approach to learning to solve simple arithmetic word problems. Our system, ARIS, analyzes each of the sentences in the problem state- ment to identify the …...

AbstractIn this paper, we analyze the quality of several commercial tools for sentiment detection. All tools are tested on nearly 30,000 short texts from various sources, such as tweets, news, …...

Classifying nouns into semantic categories (e.g., animals, food) is an important line of research in both cognitive science and natural language processing. We present a minimally supervised model for noun …...

Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this pa- per, we focus on …...

Automatically identifying anomalous newswire events is a hard problem. We discuss the com- plexity of the problem and introduce a novel technique to model events based on recursive neural networks …...

In this paper, we present a series of experiments in which we analyze the usage of graffiti style features for signaling personal gang identification in a large, online street gangs …...

AbstractIrony, a creative use of language, has received scarce attention from the computational linguistics research point of view. We propose an automatic system capable of detecting irony with good accuracy …...

Social media texts are often written in a non-standard style and include many lexical variants such as insertions, phonetic substitutions, abbreviations that mimic spoken language. The nor- malization of such …...

Wild bird watching has become a popular leisure activity in recent years. Very often, people can see birds or hear their sounds, but have no idea what kind of bird …...

Languages spoken by immigrants change due to contact with the local languages. Capturing these changes is problematic for current language technologies, which are typically developed for speakers of the standard …...

Randomized methods of significance test- ing enable estimation of the probability that an increase in score has occurred sim- ply by chance. In this paper, we examine the accuracy of …...

Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign lan- guage. In this work we provide empirical evidence …...

The sentiment captured in opinionated text provides interesting and valuable informa- tion for social media services. However, due to the complexity and diversity of linguistic representations, it is challeng- ing …...

Unlike traditional over-the-phone spoken dialog systems (SDSs), modern dialog systems tend to have visual rendering on the device screen as an additional modal- ity to communicate the system’s response to …...

Shell nouns, such as fact and problem, oc- cur frequently in all kinds of texts. These nouns themselves are unspecific, and can only be interpreted together with the shell content. …...

We present a semi-supervised approach to the problem of paradigm induction from inflection tables. Our system ex- tracts generalizations from inflection ta- bles, representing the resulting paradigms in an abstract …...

This paper describes my approach for parsing robot commands, which was task 6 at SemEval 2014. My solution is to manually create a compact unifica- tion grammar. The grammar is …...

In this paper, we present our contribution in SemEval2014 ABSA task, some supervised methods for Aspect-Based Sentiment Analysis of restaurant and laptop reviews are proposed, im- plemented and evaluated. We …...

Shared Task 1 of SemEval-2014 com- prised two subtasks on the same dataset of sentence pairs: recognizing textual en- tailment and determining textual similar- ity. We used an existing system …...

AbstractSo far predicted scenarios for Turkish dependency parsing have used a morphological disambiguator that is trained on the data distributed with the tool(Sak et al., 2008). Although models trained on …...

We develop an instance (token) based extension of the state of the art word (type) based part-of- speech induction system introduced in (Yatbaz et al., 2012). Each word instance is …...

In this paper, we explore the relationship between the human-encoded semantics of ontologies and their application to natural language processing (NLP) tasks, such as word-sense disambig- uation (WSD), for which …...

It has been shown that news events influ- ence the trends of stock price movements. However, previous work on news-driven stock market prediction rely on shallow features (such as bags-of-words, …...

In this paper we address the problem of multilingual part-of-speech tagging for resource-poor languages. We use par- allel data to transfer part-of-speech in- formation from resource-rich to resource- poor languages. …...

In order to extract entities of a fine-grained category from semi-structured data in web pages, existing information extraction sys- tems rely on seed examples or redundancy across multiple web pages. …...

Vectorial representations of words derived from large current events datasets have been shown to perform well on word similarity tasks. This paper shows vectorial representa- tions derived from substantially smaller …...

Lexical sparsity is a major challenge for machine translation into morphologically rich lan- guages. We address this problem by modeling sequences of fine-grained morphological tags in a bilingual context. To …...

Word Sense Disambiguation has been stuck for many years. In this paper we explore the use of large-scale crowdsourcing to cluster senses that are often confused by non-expert annotators. We …...

Modeling the entailment relation over sen- tences is one of the generic problems of natural language understanding. In or- der to account for this problem, we de- sign a theorem …...

In this paper, we present a hybrid approach for performing token and sentence levels Dialect Identification in Arabic. Specifi- cally we try to identify whether each to- ken in a …...

This paper describes Al-Bayan team participa- tion in SemEval-2015 Task 3, Subtask A. Task 3 targets semantic solutions for answer selec- tion in community question answering systems. We propose a …...

This paper provides the first fully au- tomatic approach for classifying clauses with respect to their aspectual properties as habitual, episodic or static. We bring together two strands of previous …...

We propose a novel framework for im- proving a word segmenter using informa- tion acquired from symbol grounding. We generate a term dictionary in three steps: generating a pseudo-stochastically seg- …...

A learner corpus is a useful resource for developing automatic assessment techniques for implementation in a computer-assisted language learning system. However, presently, learner corpora are only helpful in terms of …...

Elementary-level science exams pose sig- nificant knowledge acquisition and rea- soning challenges for automatic question answering. We develop a system that rea- sons with knowledge derived from text- books, represented …...

People vary widely in their temporal orientation—how often they emphasize the past, present, and future—and this affects their finances, health, and happiness. Traditionally, temporal orientation has been assessed by self-report …...

Readability depends on many factors rang- ing from shallow features like word length to semantic ones like coherence. We intro- duce novel graph-based coherence features based on frequent subgraphs and …...

We present an approach to Arabic auto- matic diacritization that integrates syntac- tic analysis with morphological tagging through improving the prediction of case and state features. Our best system in- …...

In this paper we present an approach for the enrichment of WSD knowledge bases with data-driven relations from a gold standard corpus (annotated with word senses, valency information, syntactic analyses, …...

We present our ongoing work on large-scale Japanese-Chinese bilingual dictionary con- struction via pivot-based statistical machine translation. We utilize statistical significance pruning to control noisy translation pairs that are induced …...

This paper presents a new algorithm to automatically solve algebra word prob- lems. Our algorithm solves a word prob- lem via analyzing a hypothesis space con- taining all possible equation …...

We propose a sentence ordering method to help compose persuasive opinions for debat- ing. In debate texts, support of an opinion such as evidence and reason typically follows the main …...

We present a case study on the role of syn- tactic structures towards resolving the Se- mantic Textual Similarity (STS) task. Al- though various approaches have been pro- posed, the …...

Model selection (picking, for example, the feature set and the regularization strength) is crucial for building high-accuracy NLP models. In supervised learning, we can es- timate the accuracy of a …...

The success of deep learning often de- rives from well-chosen operational build- ing blocks. In this work, we revise the temporal convolution operation in CNNs to better adapt it to …...

Language use is known to be influenced by personality traits as well as by socio- demographic characteristics such as age or mother tongue. As a result, it is possible to …...

Target entity disambiguation (TED), the task of identifying target entities of the same domain, has been recognized as a critical step in various important applica- tions. In this paper, we …...

In this paper, we address the challenge of creating accurate and robust part- of-speech taggers for low-resource lan- guages. We propose a method that lever- ages existing parallel data between …...

Part-of-Speech (POS) tagging is a key step in many NLP algorithms. However, tweets are difficult to POS tag because there are many phenomena that frequently appear in Twitter that are …...

We present a novel approach for unsu- pervised induction of a Reordering Gram- mar using a modified form of permuta- tion trees (Zhang and Gildea, 2007), which we apply to …...

We describe two tasks—named entity recog- nition (Task 1) and template slot filling (Task 2)—for clinical texts. The tasks leverage an- notations from the ShARe corpus, which con- sists of …...

We present a semi-supervised approach to improve dependency parsing accuracy by using bilexical statistics derived from auto-parsed data. The method is based on estimating the attachment potential of head-modifier words, …...

One of the weaknesses of current supervised word sense disambiguation (WSD) systems is that they only treat a word as a discrete en- tity. However, a continuous-space represen- tation of …...

This paper describes our participation in SemEval-2015 Task 12, and the opinion min- ing system sentiue. The general idea is that systems must determine the polarity of the sentiment expressed …...

Sentiment analysis has been a major area of interest, for which the existence of high- quality resources is crucial. In Arabic, there is a reasonable number of sentiment lexicons but …...

This paper introduces GEOS, the first au- tomated system to solve unaltered SAT ge- ometry questions by combining text un- derstanding and diagram interpretation. We model the problem of understanding …...

We use character-based statistical machine translation in order to correct user search queries in the e-commerce domain. The training data is automatically extracted from event logs where users re-issue their …...

This paper revisits the work of (Kuncham et al., 2015) which developed a statistical sandhi splitter (SSS) for agglutinative languages that was tested for Telugu and Malayalam lan- guages. Handling …...

Model combination techniques have con- sistently shown state-of-the-art perfor- mance across multiple tasks, including syntactic parsing. However, they dramat- ically increase runtime and can be diffi- cult to employ in …...

Suicide is one of major public health problems worldwide. Traditionally, suicidal ideation is assessed by surveys or interviews, which lacks of a real-time assessment of personal men- tal state. Online …...

Path queries on a knowledge graph can be used to answer compositional ques- tions such as “What languages are spoken by people living in Lisbon?”. However, knowledge graphs often have …...

One of the most common lexical transfor- mations between cognates in French and English is the presence or absence of a ter- minal “e”. However, many other transfor- mations exist, …...

 Korean is one of the well-known „pro-drop‟ languages. When translating Korean zero object into languages in which objects have to be overtly expressed, the resolution of zero object is …...

AbstractDuring the 2016 United States presidential election, politicians have increasingly used Twitter to express their beliefs, stances on current political issues, and reactions concerning national and international events. Given the …...

AbstractIn recent years there has been a surge of interest in the natural language prosessing related to the real world, such as symbol grounding, language generation, and nonlinguistic data search …...

AbstractWe propose a novel neural lemmatization model which is language independent and supervised in nature. To handle the words in a neural framework, word embedding technique is used to represent …...

Even syntactically correct sentences are per- ceived as awkward if they do not contain cor- rect punctuation. Still, the problem of au- tomatic generation of punctuation marks has been largely …...

AbstractExisting systems deliver high accuracy and F1-scores for detecting paraphrase and semantic similarity on traditional clean-text corpus. For instance, on the clean-text Microsoft Paraphrase benchmark database, the existing systems attain …...

AbstractIn most of the research studies on Author Profiling, large quantities of correctly labeled data are used to train the models. However, this does not reflect the reality in forensic …...

Distant supervision has been widely used in current systems of fine-grained entity typ- ing to automatically assign categories (en- tity types) to entity mentions. However, the types so obtained from …...

This is a Monte Carlo simulation-based study that explores the effect of the sample size of the background database on a likelihood ratio (LR)-based forensic text comparison (FTC) system built …...

AbstractThe success of long short-term memory (LSTM) neural networks in language processing is typically attributed to their ability to capture long-distance statistical regularities. Linguistic regularities are often sensitive to syntactic …...

AbstractThe paper investigates the relation between metaphoricity and distributional characteristics of verbs, introducing POM, a corpus-derived index that can be used to define the upper bound of metaphoricity of any …...

Given the limited success of medication in re- versing the effects of Alzheimer’s and other dementias, a lot of the neuroscience research has been focused on early detection, in order …...

AbstractWe assess the reliability and accuracy of (neural) word embeddings for both modern and historical English and German. Our research provides deeper insights into the empirically justified choice of optimal …...

AbstractIn this paper, we present the automatic annotation of bibliographical references’ zone in papers and articles of XML/TEI format. Our work is applied through two phases: first, we use machine …...

Evaluation of NLP methods requires test- ing against a previously vetted gold-standard test set and reporting standard metrics (ac- curacy/precision/recall/F1). The current as- sumption is that all items in a …...

How can we enable computers to automat- ically answer questions like “Who created the character Harry Potter”? Carefully built knowledge bases provide rich sources of facts. However, it remains a …...

Modeling relation paths has offered sig- nificant gains in embedding models for knowledge base (KB) completion. How- ever, enumerating paths between two en- tities is very expensive, and existing ap- …...

In this paper, we study, compare and combine two state-of-the-art approaches to automatic feature engineering: Convolution Tree Ker- nels (CTKs) and Convolutional Neural Net- works (CNNs) for learning to rank …...

AbstractAutomated grammatical error detection, which helps users improve their writing, is an important application in NLP. Recently more and more people are learning Chinese, and an automated error detection system …...

AbstractThe Index Thomisticus Treebank is the largest available treebank for Latin; it contains Medieval Latin texts by Thomas Aquinas. After experimenting on its data with a number of dependency parsers …...

AbstractTransition-based approaches based on local classification are attractive for dependency parsing due to their simplicity and speed, despite producing results slightly below the state-of-the-art. In this paper, we propose a …...

We present Emergent, a novel data-set de- rived from a digital journalism project for ru- mour debunking. The data-set contains 300 rumoured claims and 2,595 associated news articles, collected and …...

State-of-the-art sequence labeling systems traditionally require large amounts of task- specific knowledge in the form of hand- crafted features and data pre-processing. In this paper, we introduce a novel neu- …...

AbstractWe present a novel technique for Arabic morphological annotation. The technique utilizes diacritization to produce morphological annotations of quality comparable to human annotators. Although Arabic text is generally written without …...

AbstractWord sense induction (WSI) seeks to induce senses of words from unannotated corpora. In this paper, we address the WSI task for the Croatian language. We adopt the word clustering …...

In this paper, we examine the impact of employing contextual, structural information from a tree-structured document set to derive a language model. Our results show that this in- formation significantly …...

Natural language inference (NLI) is a funda- mentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it …...

Taxonomic relation identification aims to rec- ognize the ‘is-a’ relation between two terms. Previous works on identifying taxonomic re- lations are mostly based on statistical and lin- guistic approaches, but …...

Solving simple arithmetic word problems is one of the challenges in Natural Lan- guage Understanding. This paper presents a novel method to learn to use formulas to solve simple arithmetic …...

AbstractAttribution bias refers to the tendency of people to attribute successes to their own abilities but failures to external factors. In a business context an internal factor might be the …...

This paper describes team MAZA entries for the 2016 SemEval Task 11: Complex Word Identification (CWI). The task is a binary clas- sification task in which systems are trained to …...

AbstractWe propose named entity abstraction methods with fine-grained named entity labels for improving statistical machine translation (SMT). The methods are based on a bilingual named entity recognizer that uses a …...

AbstractContinuous word representations appeared to be a useful feature in many natural language processing tasks. Using fixed-dimension pre-trained word embeddings allows avoiding sparse bag-of-words representation and to train models with …...

AbstractThis paper proposes OCR++, an open-source framework designed for a variety of information extraction tasks from scholarly articles including metadata (title, author names, affiliation and e-mail), structure (section headings and …...

AbstractParallel corpora are crucial for machine translation (MT), however they are quite scarce for most language pairs and domains. As comparable corpora are far more available, many studies have been …...

AbstractBesides providing the relevant information, amusing users has been an important role of the web. Many web sites provide serendipitous (unexpected but relevant) information to draw user traffic. In this …...

Do distributional word representations en- code the linguistic regularities that theo- ries of meaning argue they should encode? We address this question in the case of the logical properties (monotonicity, …...

In this paper, we describe our approach of en- abling an interactive dialogue system to rec- ognize user emotion and sentiment in real- time. These modules allow otherwise con- ventional …...

Regularization is a critical step in supervised learning to not only address overfitting, but also to take into account any prior knowledge we may have on the features and their …...

Given a set of documents from a specific do- main (e.g., medical research journals), how do we automatically build a Knowledge Graph (KG) for that domain? Automatic identifica- tion of …...

We present an approach to simultaneously per- form semantic segmentation and prepositional phrase attachment resolution for captioned images. Some ambiguities in language can- not be resolved without simultaneously rea- soning …...

AbstractGuided by multiple heuristics, a unified taxonomy of entities and categories is distilled from the Wikipedia category network. A comprehensive evaluation, based on the analysis of upward generalization paths, demonstrates …...

This paper describes the SemEval–2016 Task 3 on Community Question Answer- ing, which we offered in English and Ara- bic. For English, we had three sub- tasks: Question–Comment Similarity (subtask …...

In this paper, we explore sentiment composi- tion in phrases that have at least one positive and at least one negative word—phrases like happy accident and best winter break. We …...

AbstractCompound words with unmarked word boundaries are problematic for many tasks in NLP and computational linguistics, including information extraction, machine translation, and syllabification. This paper introduces a simple, proof-of-concept language …...

Traditional syntax models typically lever- age part-of-speech (POS) information by constructing features from hand-tuned templates. We demonstrate that a better approach is to utilize POS tags as a reg- ularizer …...

AbstractHow-knowledge is indispensable in daily life, but has relatively less quantity and poorer quality than what-knowledge in publicly available knowledge bases. This paper first extracts task-subtask pairs from wikiHow, then …...

AbstractThe paper introduces a “train once, use many” approach for the syntactic analysis of phrasal compounds (PC) of the type XP+N like “Would you like to sit on my knee?” …...

AbstractIn this paper we explore to what extent the difficulty of listening items in an English language proficiency test can be predicted by the textual properties of the prompt. We …...

This study measures the effects of Federal Open Market Committee text content on the direction of short- and medium-term interest rate movements. Because the words relevant to short- and medium-term …...

AbstractSentiment analysis (SA) using code-mixed data from social media has several applications in opinion mining ranging from customer satisfaction to social campaign analysis in multilingual societies. Advances in this area …...

AbstractSarcasm detection has been modeled as a binary document classification task, with rich features being defined manually over input documents. Traditional models employ discrete manual features to address the task, …...

AbstractMost neural network models for document classification on social media focus on text information to the neglect of other information on these platforms. In this paper, we classify post stance …...

AbstractIn this paper, we claim that Vector Cosine ― which is generally considered one of the most efficient unsupervised measures for identifying word similarity in Vector Space Models ― can …...

AbstractThe prevalent approach to neural machine translation relies on bi-directional LSTMs to encode the source sentence. We present a faster and simpler architecture based on a succession of convolutional layers. …...

The task of document quality assessment is a highly complex one, which draws on analysis of aspects including linguistic content, document structure, fact correct- ness, and community norms. We explore …...

AbstractThis paper explores a divisive hierarchical clustering algorithm based on the well-known Obligatory Contour Principle in phonology. The purpose is twofold: to see if such an algorithm could be used …...

AbstractWe introduce a novel sub-character architecture that exploits a unique compositional structure of the Korean language. Our method decomposes each character into a small set of primitive phonetic units called …...

AbstractWe introduce a hierarchical architecture for machine reading capable of extracting precise information from long documents. The model divides the document into small, overlapping windows and encodes all windows in …...

AbstractWe present a simple method for ever-growing extraction of predicate paraphrases from news headlines in Twitter. Analysis of the output of ten weeks of collection shows that the accuracy of …...

AbstractWe propose a sentiment analyzer for the prediction of document-level sentiments of English micro-blog messages from Twitter. The proposed method is based on lexicon integrated convolutional neural networks with attention …...

AbstractStandard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear. To reward systems with real language …...

AbstractWe present a machine learning analysis of eye-tracking data for the detection of mild cognitive impairment, a decline in cognitive abilities that is associated with an increased risk of developing …...

AbstractUnderstanding common entities and their attributes is a primary requirement for any system that comprehends natural language. In order to enable learning about common entities, we introduce a novel machine …...

Automatic document classification is now a growing research topic in Natural Language Processing. Several techniques were incorporated to build a classifier that can categorize documents written in specific languages into …...

AbstractKernel methods enable the direct usage of structured representations of textual data during language learning and inference tasks. Expressive kernels, such as Tree Kernels, achieve excellent performance in NLP. On …...

AbstractIn this paper we examine methods to detect hate speech in social media, while distinguishing this from general profanity. We aim to establish lexical baselines for this task by applying …...

AbstractThis paper presents a model for Arabic morphological disambiguation based on Recurrent Neural Networks (RNN). We train Long Short-Term Memory (LSTM) cells in several configurations and embedding levels to model …...

AbstractWe describe our system for participating in SemEval-2017 Task 3 on Community Question Answering. Our approach relies on combining a rich set of various types of features: semantic and metadata. …...

AbstractWe present an unsupervised, language agnostic approach for exploiting morphological regularities present in high dimensional vector spaces. We propose a novel method for generating embeddings of words from their morphological …...

This paper presents an empirical com- parison of two strategies for Vietnamese Part-of-Speech (POS) tagging from unseg- mented text: (i) a pipeline strategy where we consider the output of a …...

AbstractThis paper describes the winning system for SemEval-2017 Task 6: #HashtagWars: Learning a Sense of Humor. Humor detection has up until now been predominantly addressed using feature-based approaches. Our system …...

AbstractRelation detection is a core component of many NLP applications including Knowledge Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural network enhanced by residual learning …...

AbstractMuch of scientific progress stems from previously published findings, but searching through the vast sea of scientific publications is difficult. We often rely on metrics of scholarly authority to find …...

AbstractAutomatic construction of large knowledge graphs (KG) by mining web-scale text datasets has received considerable attention recently. Estimating accuracy of such automatically constructed KGs is a challenging problem due to …...

AbstractIn language identification, a common first step in natural language processing, we want to automatically determine the language of some input text. Monolingual language identification assumes that the given document …...

AbstractThis paper presents a novel template-based method to solve math word problems. This method learns the mappings between math concept phrases in math word problems and their math expressions from …...

AbstractUser generated categories (UGCs) are short texts that reflect how people describe and organize entities, expressing rich semantic relations implicitly. While most methods on UGC relation extraction are based on …...

AbstractIn the paper we present a tool for lemmatization of multi-word common noun phrases and named entities for Polish called LemmaPL. The tool is based on a set of manually …...

AbstractTo learn a semantic parser from denotations, a learning algorithm must search over a combinatorially large space of logical forms for ones consistent with the annotated denotations. We propose a …...

AbstractFor the competition SemEval-2017 we investigated the possibility of performing stance classification (support, deny, query or comment) for messages in Twitter conversation threads related to rumours. Stance classification is interesting …...

AbstractWe propose an efficient method to conduct phrase alignment on parse forests for paraphrase detection. Unlike previous studies, our method identifies syntactic paraphrases under linguistically motivated grammar. In addition, it …...

AbstractThis paper describes our participation in SemEval-2017 Task 3 on Community Question Answering (cQA). The Question Similarity subtask (B) aims to rank a set of related questions retrieved by a …...

AbstractRecently, neural twitter sentiment classification has become one of state-of-thearts, which relies less feature engineering work compared with traditional methods. In this paper, we propose a simple and effective ensemble …...

AbstractThis paper presents a novel hybrid generative/discriminative model of word segmentation based on nonparametric Bayesian methods. Unlike ordinary discriminative word segmentation which relies only on labeled data, our semi-supervised model …...

AbstractWe present a novel cross-lingual transfer method for paradigm completion, the task of mapping a lemma to its inflected forms, using a neural encoder-decoder model, the state of the art …...

AbstractType-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignoring the inherent lexical ambiguity in language. Instead, we embed …...

AbstractAs the number of people receiving psycho-therapeutic treatment increases, the automatic evaluation of counseling practice arises as an important challenge in the clinical domain. In this paper, we address the …...

AbstractThis paper presents a novel approach to character identification, that is an entity linking task that maps mentions to characters in dialogues from TV show transcripts. We first augment and …...

AbstractThis paper explores the role of semantic relatedness features, such as word associations, in humour recognition. Specifically, we examine the task of inferring pairwise humour judgments in Twitter hashtag wars. …...

AbstractThis paper describes the system devel-oped for SemEval 2017 task 6: #HashTagWars -Learning a Sense of Hu-mor. Learning to recognize sense of hu-mor is the important task for language understanding …...

AbstractThis paper describes team Turing’s submission to SemEval 2017 RumourEval: Determining rumour veracity and support for rumours (SemEval 2017 Task 8, Subtask A). Subtask A addresses the challenge of rumour …...

AbstractSinglish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We …...

A tone group parser could be one of the most important components of the Taiwanese text-to-speech system. In this paper, we offered the hypothesis of tonal government to emphasis the …...

We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection. The corpus has 1.3 million sarcastic statements — …...

AbstractThe translation of pronouns presents a special challenge to machine translation to this day, since it often requires context outside the current sentence. Recent work on models that have access …...

AbstractChinese word segmentation (CWS) trained from open source corpus faces dramatic performance drop when dealing with domain text, especially for a domain with lots of special terms and diverse writing …...

AbstractThe “Capturing Discriminative Attributes” sharedtask is the tenth task, conjoint with SemEval2018. The task is to predict if a word can capture distinguishing attributes of one word from another. We …...

AbstractBook recommender systems can help promote the practice of reading for pleasure, which has been declining in recent years. One factor that influences reading preferences is writing style. We propose …...

AbstractIn this position paper, we argue that building operational automated scoring systems is a task that has disciplinary complexity above and beyond standard competitive shared tasks which usually involve applying …...

AbstractThe proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus …...

AbstractAnalyzing language in context, both from a theoretical and from a computational perspective, is receiving increased interest. Complementing the research in linguistics on discourse and information structure, in computational linguistics …...

AbstractTo comprehend an argument and fill the gap between claims and reasons, it is vital to find the implicit supporting warrants behind. In this paper, we propose a hierarchical attention …...