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An automatic compound retrieval method is pro- posed to extract compounds within a text mes- sage. It uses n-gram mutual information, relative frequency count and parts of speech as the …...

We present a novel method for segmenting the input sentence into words and assigning parts of speech to the words. It consists of a statistical language model and an efficient …...

Both full-text information retrieval and large scale parsing require text preprocessing to identify strong lexical associations in textual databases. In order to associate linguistic felicity with computational efficiency, we have …...

This paper qualifies what a true term- recognition systems would have to recog- nize. The exact bracketing of the maximal termform is then proposed as an achieve- able goal upon …...

In this paper we address the prob- lem of compound noun indexing that is about segmenting or decomposing compound nouns into promising index terms. Compound nouns as index terms that …...

We describe an implemented system for robust domain-independent syntactic parsing of English, using a unification-based grammar of part-of- speech and punctuation labels coupled with a probabilistic LR parser. We present …...

We present a novel new word extraction method from Japanese texts based on expected word frequencies. First, we compute expected word frequencies from Japanese texts using a robust stochastic N-best …...

Various strategies are proposed to identify and classify three types of proper nouns in Chinese texts. Clues from character, sentence and paragraph levels are employed to resolve Chinese personal names. …...

Information retrieval is an important ap- plication area of natural-language pro- cessing where one encounters the gen- uine challenge of processing large quanti- ties of unrestricted natural-language text. This paper …...

This paper presents a statistical parser for natural language that obtains a parsing accuracy--roughly 87% precision and 86% recall--which surpasses the best previously published results on the Wall St. Journal …...

We present a constraint-based morpholog- ical disambiguation system in which indi- vidual constraints vote on matching mor- phological parses, and disambiguation of all the tokens in a sentence is performed …...

We present a connectionist architecture and demon- strate that it can learn syntactic parsing from a cor- pus of parsed text. The architecture can represent syntactic constituents, and can learn …...

We consider the problem of assigning level numbers (weights) to hierarchically organized categories during text categorization. These levels control the ability of the categories to attract documents during the catego- …...

Named entities form the major components in a document. When we catch the fundamental entities, we can understand a document to some degree. This paper employs different types of information …...

This paper investigates the use of clustering techniques in word-sense classification, which identifies different contexts that a word was used with the same or similar sense. For simplicity, we have …...

This report describes the development of a parsing system for written Swedish and is focused on a grammar, the main component of the system, semi- automatically extracted from corpora. A …...

The paper describes an extensive experiment in inside-outside estimation of a lexicalized proba- bilistic context free grammar for German verb- final clauses. Grammar and formalism features which make the experiment …...

Grammatical relationships are an important level of natural language processing. We present a trainable approach to find these relationships through transfor- mation sequences and-error-driven learning. Our ap- proach finds grammatical …...

We present a general architecture for efficient and deterministic morphological analysis based on memory-based learning, and apply it to morphological analysis of Dutch. The system makes direct mappings from letters …...

This paper describes a first attempt at a sta- tistical model for simultaneous syntactic pars- ing and generalized word-sense disambigna- tion. On a new data set we have constructed for …...

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, …...

This paper proposes a way to improve the trans- lation quality by using information on dialogue participants that is easily obtained from out- side the translation component. We incorpo- rated …...

Information Extraction (IE) systems are com- monly based on pattern matching. Adapting an IE system to a new scenario entails the construction of a new pattern base---a time- consuming and …...

We present a simple architecture for parsing transcribed speech in which an edited-word de- tector first removes such words from the sen- tence string, and then a standard statistical parser …...

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 …...

AbstractThe reliable detection of sentence boundaries in running text is one of the first important steps in preparing an input document for translation. Although this is often neglected, it is …...

We aim at finding the minimal set of fragments which achieves maximal parse accuracy in Data Oriented Parsing. Expe- riments with the Penn Wall Street Journal treebank show that counts …...

The paper presents a statistical approach to automatic building of translation lexicons from parallel corpora. We briefly describe the pre-processing steps, a baseline iterative method, and the actual algorithm. The …...

We studied contrast and variability in a corpus of gene names to identify potential heuristics for use in performing entity identification in the molecular biology domain. Based on our findings, …...

We describe our use of an existing re- source, the Mouse Anatomical Nomen- clature, to improve a symbolic interface to anatomically-indexed gene expression data. The goal is to reduce user …...

A parsing system returning analyses in the form of sets of grammatical relations can obtain high pre- cision if it hypothesises a particular relation only when it is certain that …...

There is no blank to mark word boundaries in Chinese text. As a result, identifying words is difficult, because of segmentation ambiguities and occurrences of unknown words. Conventionally unknown words …...

This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled …...

We describe our approach to the construction and evaluation of a large-scale database called “CatVar” which contains categorial variations of English lexemes. Due to the prevalence of cross-language categorial variation …...

Several approaches have been described for the automatic unsupervised acquisi- tion of patterns for information extraction. Each approach is based on a particular model for the patterns to be acquired, …...

In this paper we report results of a supervised machine-learning approach to Chinese word segmentation. A maximum entropy tagger is trained on manually annotated data to automatically assign to Chinese …...

As the amount of on-line scientific litera- ture in the biomedical domain increases, automatic processing has become a prom- ising approach for accelerating research. We are applying syntactic parsing trained …...

We explore the idea of creating a subjectiv- ity classifier that uses lists of subjective nouns learned by bootstrapping algorithms. The goal of our research is to develop a system …...

A Natural Language Generation system produces text using as input semantic data. One of its very first tasks is to decide which pieces of information to convey in the output. …...

Automatically acquiring synonymous col- location pairs such as <turn on, OBJ, light> and <switch on, OBJ, light> from corpora is a challenging task. For this task, we can, in general, …...

This paper presents a first experience with evalu- ating sytems that address the issue of Logic Form Identification (LFi). A Gold Standard approach was used in which experts provide solutions …...

Language model based IR system proposed in recent 5 years has introduced the language model approach in the speech recognition area into the IR community and improves the performance of …...

Traditionally, coreference resolution is done by mining the reference relationships be- tween NP pairs. However, an individual NP usually lacks adequate description informa- tion of its referred entity. In this …...

Current rule induction techniques based on hard matching (i.e., strict slot-by-slot matching) tend to fare poorly in extracting information from natural language texts, which often exhibit great variations. The reason …...

In this paper, we discuss the performance of cross- lingual information extraction systems employing an automatic pattern acquisition module. This mod- ule, which creates extraction patterns starting from a user’s …...

The main problems of statistical word alignment lie in the facts that source words can only be aligned to one target word, and that the inappro- priate target word is …...

This paper presents SemFrame, a system that induces frame semantic verb classes from WordNet and LDOCE. Semantic frames are thought to have significant potential in resolving the paraphrase problem challenging …...

We investigate the impact of the precision/recall trade-off of information extraction on the per- formance of an offline corpus-based question answering (QA) system. One of our findings is that, because …...

We introduce a character-based chunking for un- known word identification in Japanese text. A major advantage of our method is an ability to detect low frequency unknown words of unrestricted …...

It is often useful to classify email accord- ing to the intent of the sender (e.g., "pro- pose a meeting", "deliver information"). We present experimental results in learn- ing to …...

The evaluative character of a word is called its semantic orientation (SO). A positive SO indicates desirability (e.g. Good, Honest) and a negative SO indicates undesirability (e.g., Bad, Ugly). This …...

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 …...

We describe a system for semantic role assignment built as part of the Senseval III task, based on an off-the-shelf parser and Maxent and Memory-Based learners. We focus on generalisation …...

This paper presents a multi-layered Question An- swering (Q.A.) architecture suitable for enhanc- ing current Q.A. capabilities with the possibility of processing complex questions. That is, questions whose answer needs …...

We participated in the SENSEVAL-3 English lexi- cal sample task and multilinguallexical sample task. We adopted a supervised learning approach with Support Vector Machines, using only the official training data …...

Part of speech taggers based on Hidden Markov Models rely on a series of hypothe- ses which make certain errors inevitable. The idea developed in this paper consists in allowing …...

In this paper we describe the Senseval 3 Basque lexical sample task. The task comprised 40 words (15 nouns, 15 verbs and 10 adjectives) selected from the Basque WordNet. 10 …...

This paper introduces a new approach to translation memories. The proposed translation technology uses linguistic analysis (morphology and parsing) to determine similarity between two source-language segments, and attempts to assemble …...

This paper describes a hybrid system for WSD, pre- sented to the English all-words and lexical-sample tasks, that relies on two different unsupervised ap- proaches. The first one selects the …...

- This paper proposes a dual-iterative method, a hierarchical inner and outer iteration method (HIO), to acquire concept words from a large-scale, un-segmented Chinese corpus. It has two levels of …...

This paper presents a novel method of semantic parsing that maps a natural language (NL) sentence to a logical form. We propose a semantic parsing method by conducting separately two …...

. Fixed multiword expressions are strings of words which to- gether behave like a single word. This research establishes a method for the automatic extraction of such expressions. Our method …...

Consumers are often forced to wade through many on-line reviews in order to make an informed prod- uct choice. This paper introduces OPINE, an unsupervised information- extraction system which mines …...

Recent systems have been developed for sentiment classification, opinion recogni- tion, and opinion analysis (e.g., detect- ing polarity and strength). We pursue an- other aspect of opinion analysis: identi- fying …...

This paper proposes a method for detect- ing errors in article usage and singular plu- ral usage based on the mass count distinc- tion. First, it learns decision lists from …...

. VSM is a mature model of text representation for categorization. Words are commonly used as dimensions of feature space of VSM, but words only provide little semantic information. Sentence …...

. A simplified N-best cascade model is put forward about Chinese organization names automatic recogni- tion. This model can do words segmentation, part-of-speech tag, chunks analysis and Chinese organization names …...

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 …...

Many information extraction (IE) systems rely on manually annotated training data to learn patterns or rules for extracting in- formation about events. Manually anno- tating data is expensive, however, and …...

We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as non- recursive noun phrases does not apply in Hebrew, and propose …...

. This paper presents a hybrid method for extracting Chinese noun phrase collocations that combines a statistical model with rule-based linguistic knowledge. The algorithm first extracts all the noun phrase …...

We address the problem of unknown word sense detection: the identification of cor- pus occurrences that are not covered by a given sense inventory. We model this as an instance …...

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 …...

This paper presents an Extended WordNet based word sense disambiguation system using a major modification to the Lesk al- gorithm. The algorithm tries to disambigu- ate nouns, verbs and adjectives. …...

This document describes the Word Sense Disam- biguation system used by Language Computer Cor- poration at English Coarse Grained All Word Task at SemEval 2007. The system is based on …...

We present a method for learning to find English to Chinese transliterations on the Web. In our approach, proper nouns are expanded into new queries aimed at maxi- mizing the …...

We describe our contribution to the SemEval task on Frame-Semantic Structure Extrac- tion. Unlike most previous systems de- scribed in literature, ours is based on depen- dency syntax. We also …...

This task consists of recognizing words and phrases that evoke semantic frames as defined in the FrameNet project (http: //framenet.icsi.berkeley.edu), and their semantic dependents, which are usually, but not always, …...

The task of identifying synonymous re- lations and objects, or Synonym Resolu- tion (SR), is critical for high-quality infor- mation extraction. The bulk of previous SR work assumed strong domain …...

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 …...

In this paper, we present a novel backward transliteration approach which can further as- sist the existing statistical model by mining monolingual web resources. Firstly, we em- ploy the syllable-based …...

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 supervised ac- quisition of semantic event frames based on a corpus of biomedical abstracts, in which the biological process of E. coli gene regulation has been …...

. It is expensive for companies to browse daily reports. Our aim is to create a system that extracts information about problems from reports. This system operates in two steps. …...

Computing precision and recall metrics for named entity tagging and resolution involves classifying text spans as true positives, false positives, or false negatives. There are many factors that make this …...

Predicting possible code-switching points can help develop more accurate methods for au- tomatically processing mixed-language text, such as multilingual language models for speech recognition systems and syntactic an- alyzers. We …...

We propose an automatic machine translation (MT) evaluation metric that calculates a sim- ilarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, we compute …...

Measure words in Chinese are used to indi- cate the count of nouns. Conventional sta- tistical machine translation (SMT) systems do not perform well on measure word generation due to …...

. This paper reports about a multi-engine approach for the development of a NER system in Bengali by combining the classifiers such as Maximum Entropy (ME), Conditional Random Field (CRF) …...

In this paper, we report experiments that explore learning of syntactic and seman- tic representations. First, we extend a state-of-the-art statistical parser to pro- duce a richly annotated tree that …...

This paper presents a probabilistic model for resolution of non-pronominal anaphora in biomedical texts. The model seeks to find the antecedents of anaphoric expres- sions, both coreferent and associative ones, …...

Query expansion has long been suggested as a technique for dealing with word mismatch problem in information retrieval. In this paper, we describe a novel query expansion method which incorporates …...

Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relation- independent extraction paradigm that is tai- lored to massive …...

In this paper we describe a methodology for detecting preposition errors in the writ- ing of non-native English speakers. Our system performs at 84% precision and close to 19% recall …...

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 …...

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 …...

This paper addresses the problem of ex- tracting the most important facts from a news article. Our approach uses syntac- tic, semantic, and general statistical fea- tures to identify the …...

Bilingual dictionaries are vital resources in many areas of natural language processing. Numerous methods of machine translation re- quire bilingual dictionaries with large cover- age, but less-frequent language pairs rarely …...

Statistical bilingual word alignment has been well studied in the context of machine trans- lation. This paper adapts the bilingual word alignment algorithm to monolingual scenario to extract collocations from …...

In this paper we address the problem of identi- fying a broad range of term variations in Japa- nese web search queries, where these varia- tions pose a particularly thorny …...

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 …...

Evaluation of word space models is usually local in the sense that it only considers words that are deemed very similar by the model. We propose a global evaluation scheme …...

We present a method for grouping the synonyms of a lemma according to its dictionary senses. The senses are defined by a large machine read- able dictionary for French, the …...

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 compare two different types of extraction patterns for automatically deriving semantic information from text: lexical patterns, built from words and word class information, and dependency patterns with syntactic informa- …...

We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, recursively induces lambda forms …...

Conditional Random Fields are commonly trained to maximize likelihood. The corresponding Fβ measure, the weighted harmonic mean of preci- sion and recall, which is established for evaluation in information retrieval …...

AbstractBlog posts containing many personal experiences or perspectives toward specific subjects are useful. Blogs allow readers to interact with bloggers by placing comments on specific blog posts. The comments carry …...

AbstractAn increasing demand for new language resources of recent EU members and accessing countries has in turn initiated the development of different language tools and resources, such as alignment tools …...

AbstractThis paper proposes the method to detect peculiar examples of the target word from a corpus. In this paper we regard following examples as peculiar examples: (1) a meaning of …...

Strategic business decision making in- volves the analysis of market forecasts. Today, the identification and aggregation of relevant market statements is done by human experts, often by analyzing doc- uments …...

AbstractCzEng 0.9 is the third release of a large parallel corpus of Czech and English. For the current release, CzEng was extended by significant amount of texts from various types …...

. In this paper, genetic algorithm (GA) is utilized to search for the appropriate fea- ture combination for constructing a maximum entropy (ME) based classifier for named entity recognition (NER). …...

In this paper, we consider the problem of gen- erating candidate corrections for the task of correcting errors in text. We focus on the task of correcting errors in preposition …...

. In this study, our purpose was to make a short summary for sentences. For ex- ample, we aimed to make a short summary “terror” for sentences “A bomb went …...

AbstractElectronic patient records (EPRs) are a valuable resource for research but for confidentiality reasons they cannot be used freely. In order to make EPRs available to a wider group of …...

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 …...

. Five years ago, a number of papers reported an experimental implementation of an Example Based Machine Translation (EBMT) system using proportional analogy. This approach, a type of analogical learning, …...

AbstractMAGEAD is a morphological analyzer and generator for Modern Standard Arabic (MSA) and its dialects. We introduced MAGEAD in previous work with an implementation of MSA and Levantine Arabic verbs. …...

AbstractThis paper presents the Multiword Expression Toolkit (mwetoolkit), an environment for type and language-independent MWE identification from corpora. The mwetoolkit provides a targeted list of MWE candidates, extracted and filtered …...

AbstractThis paper describes and evaluates a prototype quality assurance system for LSP corpora. The system will be employed in compiling a corpus of 11 M tokens for various linguistic and …...

We describe the implementation of reranking models for fine-grained opinion analysis – marking up opinion expres- sions and extracting opinion holders. The toreranking approach makes it possible model complex relations …...

Ambiguity of entity mentions and con- cept references is a challenge to mining text beyond surface-level keywords. We describe an effective method of disambi- guating surface forms and resolving them …...

This paper describes the SEMAFOR sys- tem’s performance in the SemEval 2010 task on linking events and their partici- pants in discourse. Our entry is based upon SEMAFOR 1.0 (Das …...

AbstractHistorical cabinet protocols are a useful resource which enable historians to identify the opinions expressed by politicians on different subjects and at different points of time. While cabinet protocols are …...

AbstractConceptMapper is an open source tool we created for classifying mentions in an unstructured text document based on concept terminologies (dictionaries) and yielding named entities as output. It is implemented …...

This paper focuses on the tourism-related opinion mining, including tourism-related opinion detection and tourist attraction target identification. The experimental data are blog articles labeled as in the domestic tourism category …...

AbstractThis paper presents research on building a model of grammatical error correction, for preposition errors in particular, in English text produced by language learners. Unlike most previous work which trains …...

We discuss a method for identifying se- mantic arguments of a verb from a sen- tence. It differs from existing methods by an unique feature that represents all se- mantic …...

Keyphrase extraction aims to select a set of terms from a document as a short summary of the document. Most methods extract keyphrases according to their statistical prop- erties in …...

In this paper we present a knowledge-light approach to extract a bilingual lexicon for closely related languages from compara- ble corpora. While in most related work an existing dictionary is …...

. Numerous studies have analyzed the influences of word segmentation (WS) performance on information retrieval (IR) for Mandarin Chinese and have demonstrated a non-monotonic relationship between WS accuracy and IR …...

Nowadays, many influential facts are re- ported multiple times by different sources and in different languages. This paper presents the results of an experiment on deploying cross-lingual information fu- sion …...

. In the research field of machine translation of patent documents, the issue of ac- quiring technical term translation equivalent pairs automatically from parallel patent docu- ments is one of …...

Discriminative training in query spelling cor- rection is difficult due to the complex inter- nal structures of the data. Recent work on query spelling correction suggests a two stage approach …...

AbstractWe present a method for improving word alignment quality for phrase-based statistical machine translation by reordering the source text according to the target word order suggested by an initial word …...

AbstractIn this paper we present AnIta, a powerful morphological analyser for Italian implemented within the framework of finite-state-automata models. It is provided by a large lexicon containing more than 110,000 …...

AbstractArabic is a language known for its rich and complex morphology. Although many research projects have focused on the problem of Arabic morphological analysis using different techniques and approaches, very …...

AbstractWe have been creating large-scale manual word alignment corpora for Arabic-English and Chinese-English language pairs in genres such as newsire, broadcast news and conversation, and web blogs. We are now …...

AbstractMotivation: Gold Standards for named entities are, ironically, not standard themselves. Some specify the “one perfect annotation”. Others specify “perfectly good alternatives”. The concept of Silver standard is relatively new. …...

Discovering significant types of relations from the web is challenging because of its open nature. Unsupervised algorithms are developed to extract relations from a cor- pus without knowing the relations …...

This paper presents a supervised machine learning approach to incrementally learn and segment affixes using generic background knowledge. We used Prolog script to split affixes from the Amharic word for …...

AbstractLexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of language processing tasks. Extending these resources is an expensive and time-consuming process. This …...

AbstractIn this paper, we address the problem of extracting technical terms automatically from an unannotated corpus. We introduce a technology term tagger that is based on Liblinear Support Vector Machines …...

The search in patent databases is a risky business compared to the search in other domains. A single document that is relevant but overlooked during a patent search can turn …...

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 …...

We present a method for training a semantic parser using only a knowledge base and an un- labeled text corpus, without any individually annotated sentences. Our key observation is that …...

This paper describes the systems submitted by Avaya Labs (AVAYA) to SemEval-2013 Task 2 - Sentiment Analysis in Twitter. For the constrained conditions of both the message polarity classification and …...

Derivational models are still an under- researched area in computational morphol- ogy. Even for German, a rather resource- rich language, there is a lack of large- coverage derivational knowledge. This …...

Real-word errors or context sensitive spelling errors, are misspelled words that have been wrongly converted into another word of vocabulary. One way to detect and correct real-word errors is using …...

In this paper we present a method for extracting bilingual terminologies from comparable corpora. In our approach we treat bilingual term extrac- tion as a classification problem. For classification we …...

We study question answering as a ma- chine learning problem, and induce a func- tion that maps open-domain questions to queries over a database of web extrac- tions. Given a …...

A common form of sarcasm on Twitter con- sists of a positive sentiment contrasted with a negative situation. For example, many sarcas- tic tweets include a positive sentiment, such as …...

We introduce a social media text normal- ization system that can be deployed as a preprocessing step for Machine Transla- tion and various NLP applications to han- dle social media …...

Extracting plausible transliterations from historical literature is a key issues in his- torical linguistics and other resaech fields. In Chinese historical literature, the charac- ters used to transliterate the same …...

We present a novel approach to automatic metaphor identification, that discovers both metaphorical associations and metaphorical expressions in unrestricted text. Our sys- tem first performs hierarchical graph factor- ization clustering …...

State-of-the-art fact extraction is heavily constrained by recall, as demonstrated by recent performance in TAC Slot Filling. We isolate this recall loss for NE slots by systematically analysing each stage …...

In this study, we perform an investigation of coreference resolution in the biomed- ical literature. We compare a state-of- the-art general system with a purpose- built system, demonstrating that the …...

In English text, independent clauses should be demarcated with full-stops (periods), or linked together with conjunctions. Non-native speak- ers are often prone to linking them improp- erly with commas instead …...

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 …...

Clinical texts, such as discharge sum- maries or test reports, contain a valuable amount of information that, if efficiently and effectively mined, could be used to infer new knowledge, possibly …...

AbstractThis work addresses the classification of word pairs as instances of lexical-semantic relations. The classification is approached by leveraging patterns of co-occurrence contexts from corpus data. The significance of 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 …...

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 …...

This paper presents the results of the Ix- aMed team at the SemEval-2014 Shared Task 7 on Analyzing Clinical Texts. We have developed three different sys- tems based on: a) …...

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 …...

Common-sense reasoning is important for AI applications, both in NLP and many vision and robotics tasks. We propose NaturalLI: a Natural Logic inference sys- tem for inferring common sense facts …...

AbstractWe describe a method for expanding existing dictionaries in several languages by discovering previously non-existent links between translations. We call this method triangulation and we present and compare several variations …...

This paper describes the SemEval-2014, Task 7 on the Analysis of Clinical Text and presents the evaluation results. It fo- cused on two subtasks: (i) identification (Task A) and (ii) …...

Holding non-co-located conversations while driving is dangerous (Horrey and Wickens, 2006; Strayer et al., 2006), much more so than conversations with physically present, “situated” interlocutors (Drews et al., 2004). In-car …...

Taxonomies are the backbone of many structured, semantic knowledge resources. Recent works for extracting taxonomic relations from text focused on collect- ing lexical-syntactic patterns to extract the taxonomic relations by …...

. Démonette is a lexical database whose vertices (lexical entries) and edges (morphological relations between the vertices) are annotated with morpho-semantic information. It results from an original design incorporating two …...

Distant supervision has become the lead- ing method for training large-scale rela- tion extractors, with nearly universal adop- tion in recent TAC knowledge-base pop- ulation competitions. However, there are still …...

NLP methods for automatic information access to rich technological knowledge sources like patents are of great value. One important resource for accessing this knowledge is the tech- nical terminology of …...

This paper presents a semantic parsing and reasoning approach to automatically solving math word problems. A new meaning representation language is de- signed to bridge natural language text and math …...

One aspect of ontology learning methods is the discovery of relations in textual data. One kind of such relations are causal re- lations. Our aim is to discover causations described …...

We propose FINET, a system for detect- ing the types of named entities in short inputs—such as sentences or tweets—with respect to WordNet’s super fine-grained type system. FINET generates candidate …...

Open domain targeted sentiment is the joint information extraction task that finds target mentions together with the senti- ment towards each mention from a text corpus. The task is typically …...

The lexical semantic relationships between word pairs are key features for many NLP tasks. Most approaches for automatically clas- sifying related word pairs are hindered by data sparsity because of …...

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 …...

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 …...

Thai stock brokers issue daily stock news for their customers. One broker labels these news with plus, minus and zero sign to indicate the type of recommendation. This paper proposed …...

Unstructured clinical notes are rich sources for valuable patient information. Information extraction techniques can be employed to extract this valuable information, which in turn can be used to discover new …...

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 …...

This paper describes a system developed for the disorder identification subtask within task 14 of SemEval 2015. The developed sys- tem is based on a chain of two modules, one …...

Users combine attributes and types to describe and classify entities into cate- gories. These categories are fundamen- tal for organising knowledge in a decen- tralised way acting as tags and …...

AbstractReaders usually rely on abstracts to identify relevant medical information from scientific articles. Abstracts are also essential to advanced information retrieval methods. More than 50 thousand scientific publications in PubMed …...

AbstractIn this paper we describe our work in progress in the automatic development of a taxonomy of Spanish nouns, we offer the Perl implementation we have so far, and we …...

AbstractThis paper presents the adaptation of an Entity Centric Model for Portuguese coreference resolution, considering 10 named entity categories. The model was evaluated on named e using the HAREM Portuguese …...

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 …...

AbstractIn this paper, we describe experiments on the morphosyntactic annotation of historical language varieties for the example of Middle Low German (MLG), the official language of the German Hanse during …...

AbstractThis paper addresses the problem of quantifying the differences between entity extraction systems, where in general only a small proportion a document should be selected. Comparing overall accuracy is not …...

AbstractOur work addresses automatic detection of enunciations and segments with reformulations in French spoken corpora. The proposed approach is syntagmatic. It is based on reformulation markers and specificities of spoken …...

Large volumes of electronic health records, including free-text documents, are extensively generated within various sectors of healthcare. Medical concept annotation systems are designed to enrich these documents with key concepts …...

This paper proposes a method for intra- sentential subject zero anaphora resolution in Japanese. Our proposed method utilizes a Multi-column Convolutional Neural Network (MCNN) for predicting zero anaphoric rela- tions. …...

AbstractMethods for Named Entity Recognition and Disambiguation (NERD) perform NER and NED in two separate stages. Therefore, NED may be penalized with respect to precision by NER false positives, and …...

This paper describes our approach to build a language-independent hypernym extrac- tion system, based on two modules for the SemEval-2016 Task 13 on Taxonomy Extrac- tion Evaluation (TExEval-2). This task …...

AbstractThis paper introduces LexFr, a corpus-based French lexical resource built by adapting the framework LexIt, originally developed to describe the combinatorial potential of Italian predicates. As in the original framework, …...

AbstractWe introduce a dialogue task between a virtual patient and a doctor where the dialogue system, playing the patient part in a simulated consultation, must reconcile a specialized level, to …...

Language resources that systematically orga- nize paraphrases for binary relations are of great value for various NLP tasks and have re- cently been advanced in projects like PATTY, WiseNet and …...

AbstractStreaming media provides a number of unique challenges for computational linguistics. This paper studies the temporal variation in word co-occurrence statistics, with application to event detection. We develop a spectral …...

AbstractDespite the popularity of coreference resolution as a research topic, the overwhelming majority of the work in this area focused so far on single antecedence coreference only. Multiple antecedent coreference …...

AbstractBilingual lexica are the basis for many cross-lingual natural language processing tasks. Recent works have shown success in learning bilingual dictionary by taking advantages of comparable corpora and a diverse …...

AbstractThe objective of this paper was to evaluate the performance of two statistical machine translation (SMT) systems within a cross-language information retrieval (CLIR) architecture and examine if there is a …...

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 …...

AbstractWe present an approach for answering questions that span multiple sentences and exhibit sophisticated cross-sentence anaphoric phenomena, evaluating on a rich source of such questions – the math portion of …...

AbstractWe introduce a method for error detection in automatically annotated text, aimed at supporting the creation of high-quality language resources at affordable cost. Our method combines an unsupervised generative model …...

AbstractOur goal is to construct a domain-targeted, high precision knowledge base (KB), containing general (subject,predicate,object) statements about the world, in support of a downstream question-answering (QA) application. Despite recent advances …...

AbstractA document outlier is a document that substantially deviates in semantics from the majority ones in a corpus. Automatic identification of document outliers can be valuable in many applications, such …...

AbstractThe goal of Open Information Extraction (OIE) is to extract surface relations and their arguments from natural-language text in an unsupervised, domain-independent manner. In this paper, we propose MinIE, an …...

AbstractWe have been developing an end-to-end math problem solving system that accepts natural language input. The current paper focuses on how we analyze the problem sentences to produce logical forms. …...

This work presents a comparative study between two different approaches to build an automatic classification system for Modality values in the Portuguese language. One approach uses a single multi-class classifier …...

Depending on the quality of the original document, Optical Character Recognition (OCR) can produce a range of errors – from erroneous letters to additional and spurious blank spaces. We applied …...

AbstractThe advent of social media has brought along a novel way of communication where meaning is composed by combining short text messages and visual enhancements, the so-called emojis. We describe …...

Semantic parsing offers many opportunities to improve natural language understanding. We present a semantically annotated parallel corpus for English, German, Italian, and Dutch where sentences are aligned with scoped meaning …...

AbstractThe state-of-the-art methods for relation classification are primarily based on deep neural net- works. This kind of supervised learning method suffers from not only limited training data, but also the …...

In this paper, we show how distributionally-induced semantic classes can be helpful for extracting hypernyms. We present methods for inducing sense-aware semantic classes using distributional semantics and using these induced …...

An adversarial attack is an exploitative process in which minute alterations are made to natural inputs, causing the inputs to be misclassified by neural models. In the field of speech …...

Vocabulary knowledge prediction is an important task in lexical text simplification for foreign language learners (L2 learners). However, previously studied methods that use hand-crafted rules based on one or two …...

AbstractTraditional approaches to automatic term extraction do not rely on machine learning (ML) and select the top n ranked candidate terms or candidate terms above a certain predefined cut-off point, …...

AbstractThis paper describes our approach to solve Semeval task 3: EmoContext; where, given a textual dialogue i.e. a user utterance along with two turns of context, we have to classify …...

AbstractSystems that can associate images with their spoken audio captions are an important step towards visually grounded language learning. We describe a scalable method to automatically generate diverse audio for …...

AbstractThis paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval). We considered a supervised classification-based approach to …...

AbstractIn this paper, we present an approach for classifying news articles as biased (i.e., hyperpartisan) or unbiased, based on a convolutional neural network. We experiment with various embedding methods (pretrained …...

AbstractWe present a new manually annotated corpus for broad-coverage named entity recognition for Finnish. Building on the original Universal Dependencies Finnish corpus of 754 documents (200,000 tokens) representing ten different …...

AbstractIt has been widely admitted that morphological analysis is an important step in automated text processing for morphologically rich languages. Evenki is a language with rich morphology, therefore a morphological …...

AbstractAn abundance of electronic health records (EHR) is produced every day within healthcare. The records possess valuable information for research and future improvement of healthcare. Multiple efforts have been done …...

AbstractPrior research has recognized the need to associate affective polarities with events and has produced several techniques and lexical resources for identifying affective events. Our research introduces new classification models …...

AbstractText representation plays a vital role in retrieval-based question answering, especially in the legal domain where documents are usually long and complicated. The better the question and the legal documents …...

In this paper, we propose a method of ex- tracting novel character information such as characters’ names, gender, age, occupations, and a part of relationships between characters from synopses of …...

AbstractIn this study, we construct a corpus of Japanese local assembly minutes. All speeches in an assembly were transcribed into a local assembly minutes based on the local autonomy law. …...

AbstractThis paper reports on a parsing system for Wolof based on the LFG formalism. The parser covers core constructions of Wolof, including noun classes, cleft, copula, causative and applicative sentences. …...

AbstractControllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated …...

AbstractThis work addresses the classification problem defined by sub-task A (English only) of the OffensEval 2020 challenge. We used a semi-supervised approach to classify given tweets into an offensive (OFF) …...

AbstractWe introduce a deep learning model to learn the set of enumerated job skills associated with a job description. In our analysis of a large-scale government job portal mycareersfuture.sg, we …...

AbstractWe present here Rigor Mortis, a gamified crowdsourcing platform designed to evaluate the intuition of the speakers, then train them to annotate multi-word expressions (MWEs) in French corpora. We previously …...

AbstractThis paper presents a solution for the Span Identification (SI) task in the “Detection of Propaganda Techniques in News Articles” competition at SemEval-2020. The goal of the SI task is …...

AbstractEntities are a central element of knowledge bases and are important input to many knowledge-centric tasks including text analysis. For example, they allow us to find documents relevant to a …...

AbstractIn this study, we created an imperative corpus with speech conversations from dialogues in The Big Bang Theory and with the written comments in Wikipedia’s Articles for Deletion discussions. For …...

AbstractThe notion of “in-domain data” in NLP is often over-simplistic and vague, as textual data varies in many nuanced linguistic aspects such as topic, style or level of formality. In …...

AbstractExploiting visual groundings for language understanding has recently been drawing much attention. In this work, we study visually grounded grammar induction and learn a constituency parser from both unlabeled text …...

AbstractStance detection, which aims to determine whether an individual is for or against a target concept, promises to uncover public opinion from large streams of social media data. Yet even …...

We extract definitions from text books and sci- entific publications on mathematics in both, German and English, from the sub-domain of graph theory. Mathematical texts differ from other domains because …...

AbstractBusiness Process Management (BPM) is the discipline which is responsible for management of discovering, analyzing, redesigning, monitoring, and controlling business processes. One of the most crucial tasks of BPM is …...

AbstractWe investigate both rule-based and machine learning methods for the task of compound error correction and evaluate their efficiency for North Sámi, a low resource language. The lack of error-free …...

AbstractContextualised word embeddings is a powerful tool to detect contextual synonyms. However, most of the current state-of-the-art (SOTA) deep learning concept extraction methods remain supervised and underexploit the potential of …...

AbstractProtest events provide information about social and political conflicts, the state of social cohesion and democratic conflict management, as well as the state of civil society in general. Social scientists …...

AbstractThis paper describes the first publicly available corpus of Hmong, a minority language of China, Vietnam, Laos, Thailand, and various countries in Europe and the Americas. The corpus has been …...

AbstractIn this paper, we approach summary evaluation from an applied linguistics (AL) point of view. We provide computational tools to AL researchers to simplify the process of Idea Unit (IU) …...

AbstractThe eXtreme Multi-label text Classification (XMC) problem concerns finding most relevant labels for an input text instance from a large label set. However, the XMC setup faces two challenges: (1) …...

AbstractWe present a generalized paradigm for adaptation of propositional analysis (predicate-argument pairs) to new tasks and domains. We leverage an analogy between stances (belief-driven sentiment) and concerns (topical issues with …...

This paper presents a model for German Opin- ion Role Labelling (ORL), using the data from the IGGSA-STEPS 2014 and 2016 shared tasks. We frame the problem as a token …...

AbstractDetecting disclosures of individuals’ employment status on social media can provide valuable information to match job seekers with suitable vacancies, offer social protection, or measure labor market flows. However, identifying …...

AbstractSpan-based methods with the neural networks backbone have great potential for the nested named entity recognition (NER) problem. However, they face problems such as degenerating when positive instances and negative …...

AbstractThe task of Chinese Spelling Check (CSC) is aiming to detect and correct spelling errors that can be found in the text. While manually annotating a high-quality dataset is expensive …...

AbstractWe conducted a human subject study of named entity recognition on a noisy corpus of conversational music recommendation queries, with many irregular and novel named entities. We evaluated the human …...

AbstractRecent research on multi-criteria Chinese word segmentation (MCCWS) mainly focuses on building complex private structures, adding more handcrafted features, or introducing complex optimization processes. In this work, we show that …...

AbstractSearching troves of videos with textual descriptions is a core multimodal retrieval task. Owing to the lack of a purpose-built dataset for text-to-video retrieval, video captioning datasets have been re-purposed …...

AbstractThis paper summarizes the participation of the L3i laboratory of the University of La Rochelle in the SemEval-2023 Task 2, Multilingual Complex Named Entity Recognition (MultiCoNER II). Similar to MultiCoNER …...

AbstractThis paper describes the system we used to participate in the shared task, as well as additional experiments beyond the scope of the shared task, but using its data. Our …...