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Most previous corpus-based algorithms dis- ambiguate a word with a classifier trained from previous usages of the same word. Separate classifiers have to be trained for different words. We present …...

This paper proposes a series of techniques for ex- tracting English verb–particle constructions from raw text corpora. We initially propose three basic methods, based on tagger output, chunker output and …...

We describe an approach to tagging a monolin- gual dictionary with linguistic features. In par- ticular, we annotate the dictionary entries with parts of speech, number, and tense information. The …...

* The paper comparatively studies methods of feature weighting in application to the task of cooccurrence-based classification of words according to their meaning. We explore parameter optimization of several weighting …...

We present a novel almost-unsupervised approach to the task of Word Sense Dis- ambiguation (WSD). We build sense ex- amples automatically, using large quanti- ties of Chinese text, and English-Chinese …...

We consider the impact Active Learning (AL) has on effective and efficient text cor- pus annotation, and report on reduction rates for annotation efforts ranging up until 72%. We also …...

This paper studies the impact that difficult-to- translate source-language phrases might have on the machine translation process. We formu- late the notion of difficulty as a measurable quantity; we show …...

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

A pair of sentences in different newspaper articles on an event can have one of sev- eral relations. Of these, we have focused on two, i.e., equivalence and transition. Equiv- …...

In this paper we describe an intuitionistic method for dependency parsing, where a classifier is used to determine whether a pair of words forms a dependency edge. And we also …...

AbstractWe present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a large text corpus, as …...

This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly considers conjunctions among frequent features in …...

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

AbstractIn the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known as …...

Traditional approaches to Relation Extraction from text require manually defining the rela- tions to be extracted. We propose here an ap- proach to automatically discovering relevant relations, given a large …...

Consumers increasingly rate, review and re- search products online (Jansen, 2010; Litvin et al., 2008). Consequently, websites con- taining consumer reviews are becoming tar- gets of opinion spam. While recent …...

Twitter provides access to large volumes of data in real time, but is notoriously noisy, hampering its utility for NLP. In this paper, we target out-of-vocabulary words in short text …...

Most NLP systems make predictions based solely on linguistic (textual or spo- ken) input. We show how to use visual information to make better linguistic pre- dictions. We focus on …...

This paper describes investigations into using syntactic chunk information as the basis for determining the similarity of candidate texts at the semantic level. Two approaches were con- sidered. The first …...

Domain adaptation (DA), which involves adapting a classifier developed from source to target data, has been studied intensively in re- cent years. However, when DA for word sense disambiguation (WSD) …...

AbstractWe describe the acquisition of a dialog corpus for French based on multi-task human-machine interactions in a serious game setting. We present a tool for data collection that is configurable …...

AbstractThe rise of micro-blogging in recent years has resulted in significant access to emotion-laden text. Unlike emotion expressed in other textual sources (e.g., blogs, quotes in newswire, email, product reviews, …...

AbstractRomanian has been traditionally seen as bearing three lexical genders: masculine, feminine and neuter, although it has always been known to have only two agreement patterns (for masculine and feminine). …...

This paper presents a notification system to identify in near-real-time Tweets de- scribing fire events in Australia. The sys- tem identifies fire related ‘alert words’ published on Twitter which are …...

This paper studies the problem of identifying users who use multiple userids to post in so- cial media. Since multiple userids may belong to the same author, it is hard …...

In this paper we undertake a large cross- domain investigation of sentiment domain ad- aptation, challenging the practical necessity of sentiment domain adaptation algorithms. We first show that across a …...

Recently, work in NLP was initiated on a type of opinion inference that arises when opinions are expressed toward events which have positive or negative effects on entities (+/-effect events). …...

The syntactic ambiguity of a transitive verb (Vt) followed by a noun (N) has long been a problem in Chinese parsing. In this paper, we propose a classifier to resolve …...

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

AbstractBuilding multilingual opinionated models requires multilingual corpora annotated with opinion labels. Unfortunately, such kind of corpora are rare. We consider opinions in this work as subjective or objective. In this …...

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

AbstractWhile natural language processing performance has been improved through the recognition that there is a relationship between the semantics of the verb and the syntactic context in which the verb …...

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 …...

This paper presents ongoing work to de- velop an earthquake detector based on near-real-time microblog messages from China. The system filters earthquake re- lated keywords from Sina Weibo messages available …...

This paper presents a machine learning approach to sarcasm detection on Twitter in two lan- guages – English and Czech. Although there has been some research in sarcasm detection in …...

In this paper we present a readability assessment system for Basque, ErreXail, which is going to be the preprocessing module of a Text Simplification system. To that end we compile …...

AbstractWe present a supervised method for verb sense disambiguation based on VerbNet. Most previous supervised approaches to verb sense disambiguation create a classifier for each verb that reaches a frequency …...

Domestic abuse affects people of every race, class, age, and nation. There is sig- nificant research on the prevalence and ef- fects of domestic abuse; however, such re- search typically …...

Cross-lingual text classification is a major challenge in natural language processing, since often training data is available in only one language (target language), but not avail- able for the language …...

We present a framework for using continuous- space vector representations of word meaning to derive new vectors representing the mean- ing of senses listed in a semantic network. It is …...

Answer Validation is an important step in Automatic Question Answering systems and nowadays by spreading Community Question Answering systems it is known as an impor- tant task by itself. Previous …...

We present our submission to SemEval-2015 Task 7: Diachronic Text Evaluation, in which we approach the task of assigning a date to a text as a multi-class classification problem. We …...

AbstractWe present an annotation study on a representative dataset of literal and idiomatic uses of German infinitive-verb compounds in newspaper and journal texts. Infinitive-verb compounds form a challenge for writers …...

Wikipedia is a resource of choice ex- ploited in many NLP applications, yet we are not aware of recent attempts to adapt coreference resolution to this resource. In this work, …...

In multilingual question answering, either the question needs to be translated into the docu- ment language, or vice versa. In addition to direction, there are multiple methods to per- form …...

This paper describes aspect-based polarity de- tection system for Russian, used in aspect- based sentiment analysis task (ABSA) of SemEval-2016 (Task 5, subtask 1, slot 3). The system consists of …...

Minions, a team formed of first year stu- dents in the Master of Computational Lin- guistics, started the participation at Semeval-2016 as a semester project, aiming to build a model …...

AbstractWe propose a method to decide whether two occurrences of the same noun in a source text should be translated consistently, i.e. using the same noun in the target text …...

AbstractComputerized generation of humor is a notoriously difficult AI problem. We develop an algorithm called Libitum that helps humans generate humor in a Mad Lib, which is a popular fill-in-the-blank …...

AbstractThe naive approach to annotation projection is not effective to project discourse annotations from one language to another because implicit relations are often changed to explicit ones and vice-versa in …...

AbstractQuestion answering (QA) systems are easily distracted by irrelevant or redundant words in questions, especially when faced with long or multi-sentence questions in difficult domains. This paper introduces and studies …...

AbstractIn this paper, we propose a classifier for predicting topic-specific sentiments of English Twitter messages. Our method is based on a 2-layer CNN.With a distant supervised phase we leverage a …...

AbstractThe diagnosis of serious mental health conditions such as schizophrenia is based on the judgment of clinicians whose training takes several years, and cannot be easily formalized into objective measures. …...

Relational nouns refer to an entity by virtue of how it relates to another entity. Their identification in text is a prerequisite for the correct semantic interpretation of a sentence, …...

AbstractCitations have long been used to characterize the state of a scientific field and to identify influential works. However, writers use citations for different purposes, and this varied purpose influences …...

AbstractStandard word embedding algorithms learn vector representations from large corpora of text documents in an unsupervised fashion. However, the quality of word embeddings learned from these algorithms is affected by …...

AbstractWe analyzed the outputs of multiple question answering (QA) models applied to the Stanford Question Answering Dataset (SQuAD) to identify the core challenges for QA systems on this data set. …...

AbstractInformation about the meaning of mathematical variables in text is useful in NLP/IR tasks such as symbol disambiguation, topic modeling and mathematical information retrieval (MIR). We introduce variable typing, the …...

AbstractThe exponential increase in the usage of Wikipedia as a key source of scientific knowledge among the researchers is making it absolutely necessary to metamorphose this knowledge repository into an …...

AbstractHuman trafficking is a worldwide crisis. Traffickers exploit their victims by anonymously offering sexual services through online advertisements. These ads often contain clues that law enforcement can use to separate …...

AbstractIn the following, we describe our system developed for the Semeval2019 Task 8. We fine-tuned a BERT checkpoint on the qatar living forum dump and used this checkpoint to train …...

AbstractWe propose new BERT-based methods for recognizing event causality such as “smoke cigarettes” –> “die of lung cancer” written in web texts. In our methods, we grasp each annotator’s policy …...

AbstractThe success of neural networks comes hand in hand with a desire for more interpretability. We focus on text classifiers and make them more interpretable by having them provide a …...

AbstractNatural language has recently been explored as a new medium of supervision for training machine learning models. Here, we explore learning classification tasks using language in a conversational setting – …...

AbstractWord embeddings typically represent different meanings of a word in a single conflated vector. Empirical analysis of embeddings of ambiguous words is currently limited by the small size of manually …...

AbstractLack of labelled data in the target domain for training is a common problem in domain adaptation. To overcome this problem, we propose a novel unsupervised domain adaptation method that …...

AbstractGiven the lack of an annotated corpus of non-traditional Odia literature which serves as the standard when it comes sentiment analysis, we have created an annotated corpus of Odia sentences …...

AbstractWeakly supervised text classification based on a few user-provided seed words has recently attracted much attention from researchers. Existing methods mainly generate pseudo-labels in a context-free manner (e.g., string matching), …...

AbstractGrammatical gender is assigned to nouns differently in different languages. Are all factors that influence gender assignment idiosyncratic to languages or are there any that are universal? Using cross-lingual aligned …...

AbstractDeep neural models tremendously improved machine translation. In this context, we investigate whether distinguishing machine from human translations is still feasible. We trained and applied 18 classifiers under two settings: …...

AbstractMost supervised word sense disambiguation (WSD) systems build word-specific classifiers by leveraging labeled data. However, when using word-specific classifiers, the sparseness of annotations leads to inferior sense disambiguation performance on …...

AbstractPhysical places help shape how we perceive the experiences we have there. We study the relationship between social media text and the type of the place from where it was …...

AbstractThis paper presents the description of our submission to WMT20 sentence filtering task. We combine scores from custom LASER built for each source language, a classifier built to distinguish positive …...

AbstractPersuasive dialog systems have various usages, such as donation persuasion and physical exercise persuasion. Previous persuasive dialog systems research mostly focused on analyzing the persuader’s strategies and paid little attention …...

AbstractAd hominem attacks are those that target some feature of a person’s character instead of the position the person is maintaining. These attacks are harmful because they propagate implicit biases …...

AbstractThere is content such as hate speech, offensive, toxic or aggressive documents, which are perceived differently by their consumers. They are commonly identified using classifiers solely based on textual content …...

AbstractWe investigate how Multilingual BERT (mBERT) encodes grammar by examining how the high-order grammatical feature of morphosyntactic alignment (how different languages define what counts as a “subject”) is manifested across …...

AbstractPodcast episodes often contain material extraneous to the main content, such as advertisements, interleaved within the audio and the written descriptions. We present classifiers that leverage both textual and listening …...

AbstractIn this paper, we present a system for the solution of the cross-lingual and multilingual word-in-context disambiguation task. Task organizers provided monolingual data in several languages, but no cross-lingual training …...

AbstractHumans are increasingly interacting with machines through language, sometimes in contexts where the user may not know they are talking to a machine (like over the phone or a text …...

AbstractWikipedia abstract generation aims to distill a Wikipedia abstract from web sources and has met significant success by adopting multi-document summarization techniques. However, previous works generally view the abstract as …...

AbstractNon-lexical items are expressive devices used in conversations that are not words but are nevertheless meaningful. These items play crucial roles, such as signaling turn-taking or marking stances in interactions. …...

AbstractWith the development of pre-trained models (PTMs), the performance of text classification has been continuously improved by directly employing the features generated by PTMs. However such way might not fully …...

AbstractWe test the hypothesis that discourse predictability influences Hindi syntactic choice. While prior work has shown that a number of factors (e.g., information status, dependency length, and syntactic surprisal) influence …...

AbstractMost previous methods for text data augmentation are limited to simple tasks and weak baselines. We explore data augmentation on hard tasks (i.e., few-shot natural language understanding) and strong baselines …...

AbstractLong-form answers, consisting of multiple sentences, can provide nuanced and comprehensive answers to a broader set of questions. To better understand this complex and understudied task, we study the functional …...

AbstractROCLING 2022 shared task is to design a method that can tag medical entities in sentences and then classify them into categories through an algorithm. This paper proposes three models …...

AbstractLanguage Models (LMs) often cannot be deployed because of their potential to harm users in hard-to-predict ways. Prior work identifies harmful behaviors before deployment by using human annotators to hand-write …...

AbstractProgress in summarizing long texts is inhibited by the lack of appropriate evaluation frameworks. A long summary that appropriately covers the facets of that text must also present a coherent …...

AbstractIn the context of the Multimedia Automatic Misogyny Identification (MAMI) competition 2022, we developed a framework for extracting lexical-semantic features from text and combine them with semantic descriptions of images, …...

AbstractWe tackle the task of automatically discriminating between human and machine translations. As opposed to most previous work, we perform experiments in a multilingual setting, considering multiple languages and multilingual …...

AbstractWe conduct a comparison of pre-trained encoder-only and decoder-only language models with and without continued pre-training, to detect online sexism. Our fine-tuning-based classifier system achieved the 16th rank in the …...