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In this paper, we describe the most recent implementation and evaluation of the proper noun categorization and standardization module of the DR- LINK document detection system being developed at Syracuse …...

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 …...

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 …...

In this paper, we want to describe the ar- chitecture and some of the implementation issues of a large scale category guesser for Dutch medical vocabulary. We Mso provide numerical …...

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 …...

A comparison W~LS made of vectors derived by using ordinary co-occurrence statistics from large text cor- pora and of vectors derived by measuring the inter- word distances in dictionary definitions. …...

Previous work on automated dictionary construction for information extraction has relied on annotated text corpora. However, annotating a corpus is time-consuming and difficult. We propose that conceptual patterns for information …...

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 …...

Implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. Mr. as an indicator of a PERSON entity type). …...

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- …...

In this paper we discuss the use of discourse con- text in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics …...

In this paper wc discuss the use of discourse con- text in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics …...

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 presents a new model for word align- ments between parallel sentences, which allows one ~o accurately estimate different parameters, in a computationally efficient way. An applica- tion of …...

We investigated both English and Chinese ad-hoc information retrieval (IR). Part of our objectives is to study the use of term, phrasal and topical concept level evidence, either individually or …...

The study presented here relies on the integrated use of different kinds of knowledge in order to improve first-guess accuracy in non-word context-sensitive correction for general unrestricted texts. State of …...

The study presented here relies on the integrated use of different kinds of knowledge in order to improve first-guess accuracy in non-word context-sensitive correction for general unrestricted texts. State of …...

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 …...

AbstractA statistical method for compound noun decomposition is presented. Previous studies on this problem showed some statistical information are helpful. But applying statistical information was not so systemic that performance …...

This article describes the current state of syntactic analysis of Estonian using Constraint Grammar. Constraint Gram- mar framework divides parsing into two different modules: morphological disam- biguation and determination of …...

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 …...

AbstractThis paper proposes a method for lexical transfer ambiguity resolution using corpus and conceptual information. Previous researches have restricted the use of linguistic knowledge to the lexical level. Since the …...

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, …...

We describe a segmentation component that utilizes minimal syntactic knowledge to produce a lattice of word candidates for a broad coverage Japanese NL parser. The segmenter is a finite state …...

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 …...

We submitted four systems to the Japanese dictionary-based lexical-sample task of SENSEVAL-2. They were i) the support vector machine method ii) the simple Bayes method, iii) a method combining the …...

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 …...

We present WASP-Bench: a novel approach to Word Sense Disambiguation, also providing a semi-automatic environment for a lexicographer to compose dictionary entries based on corpus evidence. For WSD, involving lexicographers …...

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 …...

This paper describes a bootstrapping al- gorithm called Basilisk that learns high- quality semantic lexicons for multiple cate- gories. Basilisk begins with an unannotated corpus and seed words for each …...

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 …...

While the corpus-based research relies on hu- man annotated corpora, it is often said that a non-negligible amount of errors remain even in frequently used corpora such as Penn Treebank. …...

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 …...

This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated …...

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 …...

An unsupervised method for word sense disam- biguation using a bilingual comparable corpus was developed. First, it extracts statistically significant pairs of related words from the corpus of each lan- …...

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 …...

A meaningful noun-verb word-pair in a sentence is called a noun-verb event-frame (NVFE). Previously, we have developed an NVEF word-pair identifier to demonstrate that NVEF knowledge can be used effectively …...

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 …...

Automatic Multi-word Units Extraction is an important issue in Natural Language Processing. This paper has proposed a new statistical method based on a large-scale balanced corpus to extract multi-word units. …...

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 …...

This paper describes a method for learn- ing the countability preferences of English nouns from raw text corpora. The method maps the corpus-attested lexico-syntactic properties of each noun onto a …...

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, …...

In this paper we demonstrate methods of im- proving both the recall and the precision of au- tomatic methods for extraction of hyponymy (IS A) relations from free text. By …...

We propose the use of Lexicalized Tree Adjoining Grammar (LTAG) as a source of features that are useful for reranking the output of a statistical parser. In this paper, we …...

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 …...

We propose a multiple-document summa- rization system with user interaction. Our system extracts keywords from sets of docu- ments to be summarized and shows the key- words to a user …...

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 word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The problem …...

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 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 …...

This paper investigates the application of Max- imum Entropy Markov Models to semantic role labelling. Syntactic chunks are labelled according to the semantic role they fill for sentence verb pred- …...

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 …...

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 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 …...

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 …...

In this paper we describe searchable trans- lation memories, which allow translators to search their archives for possible trans- lations of phrases. We describe how sta- tistical machine translation can …...

- 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 …...

This paper proposes an alignment adaptation approach to improve domain-specific (in-domain) word alignment. The basic idea of alignment adaptation is to use out-of-domain corpus to improve in-domain word alignment results. …...

This paper describes a novel system for acquiring adjectival subcategorization frames (SCFs) and associated frequency information from English corpus data. The system incorporates a decision-tree classifier for 30 SCF types …...

. 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 …...

. 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- …...

German has a productive morphology and allows the creation of complex words which are often highly ambiguous. This paper reports on the development of a head-lexicalized PCFG for the disam- …...

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 …...

. 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 …...

. 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 …...

We propose a method for compiling bi- lingual terminologies of multi-word terms (MWTs) for given translation pairs of seed terms. Traditional methods for bi- lingual terminology compilation exploit parallel texts, …...

. In this paper, a fast automatic NP alignment technique developed for MetaMorpho TM is presented. MetaMorpho TM is an EBMT-based translation memory that stores not only full sentence pairs …...

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 …...

. AutoCor is a method for the automatic acquisition and classification of corpora of documents in closely-related languages. It is an extension and enhancement of CorpusBuilder, a system that automatically …...

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 …...

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 present a web mining method for discov- ering and enhancing relationships in which a specified concept (word class) participates. We discover a whole range of relationships focused on the …...

We present a corpus-based supervised lear- ning system for coarse-grained sense disam- biguation. In addition to usual features for training in word sense disambiguation, our system also uses Base Level …...

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. …...

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 …...

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, …...

In this paper, we empirically demonstrate what we call the domain restriction hy- pothesis, claiming that semantically re- lated terms extracted from a corpus tend to be semantically coherent. We …...

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 …...

We present results that show that incorporat- ing lexical and structural semantic informa- tion is effective for word sense disambigua- tion. We evaluated the method by using pre- cise information …...

This paper proposes a method for auto- matic POS (part-of-speech) guessing of Chinese unknown words. It contains two models. The first model uses a machine- learning method to predict the …...

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 …...

Knowing the degree of antonymy between words has widespread applications in natural language processing. Manually-created lexi- cons have limited coverage and do not include most semantically contrasting word pairs. We …...

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 …...

We describe an entirely statistics-based, unsupervised, and language- independent approach to multilingual information retrieval, which we call La- tent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related …...

We develop a data set of Malay lexemes la- belled with count classifiers, that are attested in raw or lemmatised corpora. A maximum entropy classifier based on simple, language- inspecific …...

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 …...

This paper presents a method for mining potential troubles or obstacles related to the use of a given object. Some exam- ple instances of this relation are ⟨medicine, side effect⟩ …...

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) …...

Annotated corpora are only useful if their annotations are consistent. Most large-scale annotation efforts take special measures to reconcile inter-annotator disagreement. To date, however, no-one has investigated how to automatically …...

This study presents a method to automat- ically acquire paraphrases using bilingual corpora, which utilizes the bilingual de- pendency relations obtained by projecting a monolingual dependency parse onto the other …...

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 …...

We present a graph-based semi-supervised la- bel propagation algorithm for acquiring open- domain labeled classes and their instances from a combination of unstructured and struc- tured text sources. This acquisition …...

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 …...

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 …...

Retrieving answer containing passages is a chal- lenging task in Question Answering. In this pa- per we describe a novel query expansion method which aims to rank the answer containing …...

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 …...

In this paper, we explore ways of improv- ing an inference rule collection and its ap- plication to the task of recognizing textual entailment. For this purpose, we start with …...

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 a method for detecting and correcting multiple real-word spelling er- rors using the Google Web 1T 3-gram data set and a normalized and modified ver- sion of the …...

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 …...

This paper presents three successful tech- niques to translate prepositions heading verbal complements by means of rich lin- guistic information, in the context of a rule-based Machine Translation system for …...

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 …...

AbstractWe describe a corpus of numerical expressions, developed as part of the NUMGEN project. The corpus contains newspaper articles and scientific papers in which exactly the same numerical facts are …...

AbstractParallel corpora are indispensable resources for a variety of multilingual natural language processing tasks. This paper presents a technique for fully automatic construction of constantly growing parallel corpora. We propose …...

We present a novel approach to relation ex- traction that integrates information across doc- uments, performs global inference and re- quires no labelled text. In particular, we tackle relation extraction …...

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 …...

We propose a simple but effective method for enriching dictionary definitions with images based on image searches. Vari- ous query expansion methods using syn- onyms/hypernyms (or related words) are evaluated. …...

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 report a multiobjective optimization (MOO) based technique to select the appropriate subset of votes per classifier in an ensemble system. We hypothesize that the reliability …...

AbstractThis paper describes an interface that was developed for processing large amounts of human judgments of linguistically annotated data. Fred’s Reusable Evaluation Device (“Fred”) provides administrators with a tool to …...

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. …...

As a participant in TempEval-2, we ad- dress the temporal relations task consist- ing of four related subtasks. We take a su- pervised machine-learning technique us- ing Markov Logic in …...

We describe a new unsupervised approach for synonymy discovery by aligning para- phrases in monolingual domain corpora. For that purpose, we identify phrasal terms that convey most of the concepts …...

This paper proposes a method that extracts paraphrases from search engine query logs. The method first extracts paraphrase query-title pairs based on an assumption that a search query and its …...

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 …...

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 …...

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 …...

We present a named entity recognition (NER) system for extracting product attributes and values from listing titles. Information extrac- tion from short listing titles present a unique challenge, with the …...

. 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 …...

Information published in online stock invest- ment message boards, and more recently in stock microblogs, is considered highly valu- able by many investors. Previous work fo- cused on aggregation of …...

This paper investigates the application of an existing seed-based minimally super- vised learning algorithm to different so- cial domains exhibiting different proper- ties of the available data. A systematic analysis …...

We consider the problem of performing learn- ing and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference procedure based …...

In this paper we introduce an unsupervised learning approach for WordNet construction. The whole construction method is an Expecta- tion Maximization (EM) approach which uses Princeton WordNet 3.0 (PWN) and …...

AbstractOne of the main resources used for the task of bilingual lexicon extraction from comparable corpora is : the bilingual dictionary, which is considered as a bridge between two languages. …...

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. …...

Kernel based methods dominate the current trend for various relation extraction tasks including protein-protein interaction (PPI) extraction. PPI information is critical in un- derstanding biological processes. Despite considerable efforts, previously …...

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 …...

This paper brings up an important issue, polysemy problems, in a Chinese to Taiwanese TTS (text-to-speech) system. Polysemy means there are words with more than one meaning or pronunciation, such …...

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 …...

This paper presents an identification framework for extracting Tibetan base noun phrase (NP). The framework includes two phases. In the first phase, Chinese base NPs are extracted from all Chinese …...

Search log sessions contain a large number of paraphrases contributed by users during query rewriting. However, it is a big challenge to distinguish paraphrases from the simply related queries in …...

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 …...

We present a method which exploits auto- matically generated scientific discourse an- notations to create a content model for the summarisation of scientific articles. Full pa- pers are first automatically …...

Online resources, such as Wiktionary, provide an accurate but incomplete source of idiomatic phrases. In this paper, we study the problem of automatically identifying idiomatic dictio- nary entries with such …...

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 …...

Social scientists are increasingly using the vast amount of text available on social me- dia to measure variation in happiness and other psychological states. Such studies count words deemed to …...

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 …...

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 …...

Identification, Alignment, and Tranlsation of Relational Adjectives from Comparable Corpora In this paper, we extract French relational adjectives and automatically align them with the nouns they are derived from by …...

Interpreting anaphoric shell nouns (ASNs) such as this issue and this fact is essential to understanding virtually any substantial natural language text. One obstacle in developing methods for automatically interpreting …...

For participating in the SemEval 2013 chal- lenge of recognition and classification of drug names, we adapted our chemical en- tity recognition approach consisting in Condi- tional Random Fields for …...

We propose a minimally supervised method for multilingual paraphrase extraction from definition sentences on the Web. Hashimoto et al. (2011) extracted paraphrases from Japanese definition sentences on the Web, as- …...

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 …...

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 …...

In this paper we propose a two-stage method to acquire contradiction relations between typed lexico-syntactic patterns such as Xdrug prevents Ydisease and Ydisease caused by Xdrug. In the first stage, …...

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 …...

AbstractThis paper addresses vector space models of prepositions, a notoriously ambiguous word class. We propose a rank-based distance measure to explore the vector-spatial properties of the ambiguous objects, focusing on …...

Wikipedia’s link structure is a valuable resource for natural language processing tasks, but only a fraction of the concepts mentioned in each article are annotated with hyperlinks. In this paper, …...

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 reports on the development of a hy- brid and simple method based on a machine learning classifier (Naive Bayes), Word Sense Disambiguation and rules, for the automatic assignment …...

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 …...

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 presents an initial investigation on how to distinguish collocations from free combinations. The assumption is that, while free combinations can be literally translated, the overall meaning of collocations …...

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 …...

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 …...

. Our work addresses the automatic detection of paraphrastic rephrasing in spoken corpus. The proposed approach is syntagmatic. It is based on paraphrastic rephrasing markers and the specificities of the …...

AbstractBilingual dictionaries are the key component of the cross-lingual similarity estimation methods. Usually such dictionary generation is accomplished by manual or automatic means. Automatic generation approaches include to exploit parallel …...

In this paper, we propose and demonstrate Exploratory Relation Extraction (ERE), a novel approach to identifying and extracting relations from large text corpora based on user-driven and data-guided incremental exploration. …...

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) …...

. We present a medical question answering approach, called MEANS. This approach relies on natural language processing techniques to extract medical entities and relations from the user questions and medical …...

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 …...

Translation retrieval aims to find the most likely translation among a set of target-language strings for a given source-language string. Previous studies consider the single-best translation as a query for …...

Search engines are increasingly relying on large knowledge bases of facts to provide direct answers to users’ queries. How- ever, the construction of these knowledge bases is largely manual and …...

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) …...

Opinions may be expressed implicitly via inference over explicit sentiments and events that positively/negatively affect en- tities (goodFor/badFor events). We in- vestigate how such inferences may be exploited to improve …...

. 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 …...

Derivationally related lemmas like friendN – friendlyA – friendshipN are derived from a common stem. Frequently, their meanings are also systematically related. However, there are also many examples of derivationally …...

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 …...

In this paper, we present an unsupervised two-phase approach to extract keywords from Arabic documents that combines statistical analysis and linguistic information. The first phase detects all the N-grams that …...

We propose an unsupervised approach to constructing templates from a large collec- tion of semantic category names, and use the templates as the semantic representa- tion of categories. The main …...

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 …...

AbstractSarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not just automatically but often for humans too. It has an important effect on sentiment, but …...

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 …...

Many events referred to on Twitter are of a periodic nature, characterized by roughly constant time intervals in between occur- rences. Examples are annual music fes- tivals, weekly television programs, …...

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 …...

This paper presents a Constraint Grammar- based pedagogical proofing tool for Danish. The system recognizes not only spelling errors, but also grammatical errors in otherwise correctly spelled words, and categorizes …...

This paper presents a novel technique for empty category (EC) detection using dis- tributed word representations. A joint model is learned from the labeled data to map both the distributed …...

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 …...

We propose a novel method for acquiring entailment pairs of binary patterns on a large-scale. This method exploits the tran- sitivity of entailment and a self-training scheme to improve the …...

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 …...

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 …...

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 …...

AbstractThis paper provides a new method to correct annotation errors in a treebank. The previous error correction method constructs a pseudo parallel corpus where incorrect partial parse trees are paired …...

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 …...

AbstractMotivated by the adage that a “picture is worth a thousand words” it can be reasoned that automatically enriching the textual content of a document with relevant images can increase …...

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 …...

AbstractThe paper describes automatic definition finding implemented within the leading corpus query and management tool, Sketch Engine. The implementation exploits complex pattern-matching queries in the corpus query language (CQL) and …...

AbstractWe address the problem of inducing word alignment for language pairs by developing an unsupervised model with the capability of getting applied to other generative alignment models. We approach the …...

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 …...

The challenges of Machine Reading and Knowledge Extraction at a web scale re- quire a system capable of extracting diverse information from large, heterogeneous cor- pora. The Open Information Extraction …...

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 …...

Many downstream NLP tasks can benefit from Open Information Extraction (Open IE) as a semantic representation. While Open IE sys- tems are available for English, many other languages lack such …...

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 …...

This paper describes our approach to partici- pate on SemEval2016 Task12: Clinical Tem- pEval. Our system was based on IBEnt, a framework to identify chemical entities and their relations in …...

Can we train a system that, on any new input, either says “don’t know” or makes a prediction that is guaranteed to be cor- rect? We answer the question in …...

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 …...

AbstractSentiment shifters, i.e., words and expressions that can affect text polarity, play an important role in opinion mining. However, the limited ability of current automated opinion mining systems to handle …...

AbstractDiscourse parsing is a challenging task in NLP and plays a crucial role in discourse analysis. To enable discourse analysis for Hindi, Hindi Discourse Relations Bank was created on a …...

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 …...

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. …...

AbstractThis paper presents an approach to generating common sense knowledge written in raw English sentences. Instead of using public contributors to feed this source, this system chose to employ expert …...

AbstractThis study presents SMILLE, a system that draws on the Noticing Hypothesis and on input enhancements, addressing the lack of salience of grammatical infor mation in online documents chosen by …...

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 …...

CoreNet is a lexico-semantic network of 73,100 Korean word senses, which are categorized under 2,937 semantic categories organized in a taxonomy. Recently, to foster the more widespread use of CoreNet, …...

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 …...

AbstractWe study the problem of textual relation embedding with distant supervision. To combat the wrong labeling problem of distant supervision, we propose to embed textual relations with global statistics of …...

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 …...

AbstractWe develop CALM, a coordination analyzer that improves upon the conjuncts identified from dependency parses. It uses a language model based scoring and several linguistic constraints to search over hierarchical …...

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, …...

AbstractWe present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et al., 2017). Contrary to …...

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 …...

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 …...

AbstractWith the epidemic of COVID-19, verifying the scientifically false online information, such as fake news and maliciously fabricated statements, has become crucial. However, the lack of training data in the …...

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 …...

AbstractThis paper proposes an iterative inference algorithm for multi-hop explanation regeneration, that retrieves relevant factual evidence in the form of text snippets, given a natural language question and its answer. …...

AbstractSimilarity search is to find the most similar items for a certain target item. The ability of similarity search at large scale plays a significant role in many information retrieval …...

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. …...

Typical systems for analyzing users’ opinions from online product reviews have been re- searched and developed successfully. How- ever, it is still hard to obtain sufficient user opinions when many …...

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. …...

AbstractPublic works procurements move US$ 10 billion yearly in Brazil and are a preferred field for collusion and fraud. Federal Police and audit agencies investigate collusion (bid-rigging), over-pricing, and delivery …...

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 …...

AbstractWe study the problem of learning an event classifier from human needs category descriptions, which is challenging due to: (1) the use of highly abstract concepts in natural language descriptions, …...

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) …...

AbstractCross-lingual word embedding (CWE) algorithms represent words in multiple languages in a unified vector space. Multi-Word Expressions (MWE) are common in every language. When training word embeddings, each component word …...

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 …...

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 …...

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 …...

AbstractThis paper describes PTST, a source-free unsupervised domain adaptation technique for sequence tagging, and its application to the SemEval-2021 Task 10 on time expression recognition. PTST is an extension of …...

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 …...

AbstractBasic-level categories (BLC) are an important psycholinguistic concept introduced by Rosch et al. (1976); they are defined as the most inclusive categories for which a concrete mental image of the …...

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) …...

AbstractA major drawback of modern neural OpenIE systems and benchmarks is that they prioritize high coverage of information in extractions over compactness of their constituents. This severely limits the usefulness …...

AbstractThe study of metaphors in media discourse is an increasingly researched topic as media are an important shaper of social reality and metaphors are an indicator of how we think …...

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) …...

AbstractAnalogy-making gives rise to reasoning, abstraction, flexible categorization and counterfactual inference – abilities lacking in even the best AI systems today. Much research has suggested that analogies are key to …...

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 …...

AbstractCrowdsourcing the collection of speech provides a scalable setting to access a customisable demographic according to each dataset’s needs. The correctness of speaker metadata is especially relevant for speaker-centred collections …...

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 …...

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 …...

AbstractSampling-based decoding strategies are widely employed for generating text from probabilistic models, yet standard ancestral sampling often results in text that is degenerate or incoherent. To alleviate this issue, various …...

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 …...

AbstractWord sense disambiguation is an NLP task embedded in different applications. We propose to evaluate its contribution to the automatic translation of French texts into pictographs, in the context of …...