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Since the release of the FrameNet (Baker, Fillmore, and Lowe 1998) and Propbank (Palmer, Gildea, and Kingsbury 2005) corpora, there has been a large amount of work on statistical models for semantic role labeling. Most of this work relies heavily on local classifiers: ones that decide the semantic role of each phrase i... | 0 |
According to the Center for disease Control and prevention (CDC) there is one death by suicide in the United States every twelve minutes (Stone et al., 2018) . Worldwide, suicide is one of the main causes of death for those with ages between 15 and 29 years old, and Europe is the continent with the highest suicide mort... | 0 |
People understand narratives of everyday life by capitalising on their commonsense knowledge. They can easily reason about unobserved causes and effects in relation to the events described in narratives, as well as plausible characteristics and mental states of the involved persons. Although this kind of reasoning seem... | 0 |
Recognition of temporal expressions 1 is a task of proper identification of phrases with temporal semantics in running text. After several evaluation campaigns targeted at temporal processing of text, such as MUC, ACE TERN and TempEval-1 (Verhagen et al., 2007) , the recognition and normalization task has been again ne... | 0 |
talks of "the spectacular growth and pervasiveness of the World Wide Web" leading to a "democratization" of Machine Translation (MT) which has "profoundly transformed the MT business". The availability of free on-line MT systems, since CompuServe's initial experiments in 1994 (Flanagan, 1996) and then more significantl... | 0 |
The use of social media has seen a sharp upward trend in recent years. It plays a big role in forming and shaping the views of people on various issues. From sharing facts and opinions to voicing dis sent and grievances, the platform has gained popu larity amongst many users (Nielsen and Schrøder, 2014) . Twitter is a ... | 0 |
Statistical machine translation (SMT) has seen a resurgence in popularity in recent years, with progress being driven by a move to phrase-based and syntax-inspired approaches. Progress within these approaches however has been less dramatic. We believe this is because these frequency count based 1 models cannot easily i... | 0 |
Translation is... what translators do! This punch line is from none other than the prominent computational linguist Martin Kay, who goes on to explain that translation is essentially a communicational, rather than linguistic, process. Although translation involves a major linguistic component, communication is the driv... | 0 |
Semantic knowledge is often represented declaratively in resources created by linguistic experts. In this work, we strive to exploit such knowledge in a principled, unified, and intuitive way. An example resource where a wide variety of knowledge has been encoded over a long period of time is the FrameNet lexicon (Fill... | 0 |
In many areas of computational linguistics, there is a tension between a need for powerful formalisms and the desire for efficient processing. Expressive formalisms are useful because they allow us to specify linguistic facts at the right level of abstraction, and in a way that supports the creation and maintenance of ... | 0 |
Sentence fusion is the task of combining several independent sentences into a single coherent text (Barzilay and McKeown, 2005) . Sentence fusion is important in many NLP applications, including retrieval-based dialogue (Song et al., 2018; Yan and Zhao, 2018) , text summarization (Barzilay and McKeown, 2005; Bing et al... | 0 |
ConceptNet ) is a semantic network which contains general commonsense facts about the world, e.g. Birds can fly or Computers are used for sending e-mails (Liebermann, 2008) . It originates from the crowdsourcing project Open Mind Common Sense (Speer et al., 2008) that acquired commonsense knowledge from contributions o... | 0 |
This paper describes a hybrid Chinese word segmenter that participated in the closed track of the Peking University Corpus in the Second International Chinese Word Segmentation Bakeoff. This segmenter is still in its early stage of development and is being developed as part of a larger Chinese unknown word resolution s... | 0 |
Text preprocessing and preparation plays an important role in all NLP tasks. Uysal and Gunal (2014) show that choosing the appropriate preprocessing tasks significantly improves classification accuracy. Therefore in any NLP research project, experimenting with different preprocessing schemes is an important component o... | 0 |
Monolingual word alignment aims to align words or phrases with similar meaning in two sentences that are written in the same language. It is useful for improving the interpretability in natural language understanding tasks, including semantic textual similarity (Li and Srikumar, 2016) and question answering (Yao, 2014)... | 0 |
CIST system has participated Track 1: Multilingual Multi-document Summarization in ACL MultiLing 2013 workshop. It could deal with all ten languages: Arabic, Chinese, Czech, English, French, Greek, Hebrew, Hindi, Romanian and Spanish. It summarizes every topic containing 10 texts and generates a summary in plain text, ... | 0 |
As spoken dialogue systems are designed to perform ever more elaborate tasks, the need for mixed-initiative interaction necessarily grows. Mixed-initiative interaction, where agents (both artificial and human) may freely contribute to reach a solution efficiently, has long been a focus of dialogue systems research (All... | 0 |
A pun is a form of wordplay in which one signifier (e.g., a word or phrase) suggests two or more meanings by exploiting polysemy, or phonological similarity to another signifier, for an intended humorous or rhetorical effect. The study of puns can be seen as a respectable research topic in traditional linguistics and t... | 0 |
This paper describes two systems entered in SemEval-2007 task #4: Classification of Semantic Relations between Nominals. A key contribution of this research is that we examine the compatibility of noun compound (NC) interpretation methods over the extended task of nominal classification, to gain empirical insight into ... | 0 |
Most advocates (Pereira, 2000; Bod et al., 2003) and critics (Chomsky, 1957; Fong et al., 2013 ) of a probabilistic view of grammatical knowledge have assumed that this view identifies the grammatical status of a sentence directly with the probability of its occurrence. By contrast, we seek to characterize grammatical ... | 0 |
BLEU (Papineni et al. 2002 ) is a metric that is widely used to evaluate Natural Language Processing (NLP) systems which produce language, especially machine translation (MT) and Natural Language Generation (NLG) systems. Because BLEU itself just computes word-based overlap with a gold-standard reference text, its use ... | 0 |
Speech and text corpora augmented with linguistic annotations have become essential to everyday NLP. In the realm of discourse-related annotation, which we are interested in, linguistic annotation is still mostly a manual effort. Thus, the availability of coding tools that facilitate a human coder's task has become par... | 0 |
Taxonomies provide a natural and intuitive means of organizing information, from the biological taxonomies of the Linnaean system to the layout of supermarkets and bookstores to the organizational structure of companies. Taxonomies also provide the structural backbone for ontologies in computer science, from common-sen... | 0 |
In the course of the last two decades, significant progress has been made with regard to the automatic extraction of lexical semantic knowledge from largescale text corpora. Most work relies on the distributional hypothesis of meaning (Harris, 1954) , which states that words that appear within the same contexts tend to... | 0 |
In this paper, we describe some new extensions to the data-driven MT system developed at DCU, MaTrEx (Machine Translation using examples), subsequent to our participation at IWSLT 2006 (Stroppa and Way, 2006) .Firstly, we extend our word packing technique (Ma et al., 2007a) to Japanese and Arabic. Secondly, we demonstr... | 0 |
Paraphrasing, the act of generating the same semantic content as the source in the same language, can help gain performance improvements in many NLP applications. Examples include generating query variants or pattern alternatives for information retrieval, information extraction or question answering systems, creating ... | 0 |
We assume, together with [l ] that POS tagging is esscntially a syntactically-based phenomenon and that by cle,•erly coupling stochnstic and Jinguisric processing one should be able to remedv some if not all of the drawbacks usually associated with the two approaches, when used in isolation. However, as •will be shown ... | 0 |
Machine reading comprehension (MRC) aims to develop AI models that can answer questions for text documents. Recently, the performance of MRC in public datasets has been improved dramatically due to the advanced pre-trained models, such as BERT (Devlin et al., 2019) , RoBERTa and ALBERT (Lan et al., 2019) .However, pre-... | 0 |
In this paper, we will present the core aspects of the generation component of our speech to speech dialogue translation system, the domain of which is hotel reservation. The whole system consists of five modules: speech recognizer, translator, dialogue manager, generator and speech synthesizer. And the system takes th... | 0 |
Finite state automata (FSAs) and weighted finite state automata (WFSAs) are widely used in language and speech processing (Kaplan & Kay, 1981; Mohri, 1997; Beesley & Karttunen, 2003) . They permit, among others, the fast processing of input strings and can be easily modified and combined by well defined operations. Mos... | 0 |
Human beings remember useful and important information and gradually forget old and unimportant information in order to accommodate new information. Under the constraint of memory capacity, it is important to have a learning mechanism that utilizes memory to store and to retrieve information efficiently and flexibly wi... | 0 |
Text simplification (TS) is aimed at reducing the reading and grammatical complexity of text while retaining the meaning and grammaticality (Chandrasekar and Bangalore, 1997) . This is usually achieved by a series of transformations at the lexical and syntactic level. A number of systems in the recent years have approa... | 0 |
This paper describes the information extraction techniques developed in the framework of the participation of IRISA-TexMex to BioNLP-ST13. For this first participation, we submitted runs for three tasks, concerning entity detection and categorization (Bacterial Biotope subtask 1, BB1), and relation detection and catego... | 0 |
A fundamental issue for many tasks in the field of Computational Linguistics and Language Technologies in general is the lack of Language Resources (LRs) to tackle them successfully, especially for some languages and domains. It is the so-called LRs bottleneck.Our objective is to build a factory of LRs that automates t... | 0 |
The development of large-scale language models (sometimes called foundation models) is dramatically changing what technology can achieve and support (Bommasani et al., 2021) . Language models like GPT3 (Brown et al., 2020) and Meena (Adiwardana et al., 2020) have led to an increasing interest in how these new technolog... | 0 |
Just as neural machine translation (NMT) systems have achieved tremendous benchmark results, they have been proven brittle when faced with irregular inputs such as noisy text (Belinkov and Bisk, 2018; Michel and Neubig, 2018) or adversarial inputs (Cheng et al., 2020) . Among such errors, mistranslation of numerical te... | 0 |
Data-to-text generation refers to the task of automatically generating text from non-linguistic data (Reiter and Dale, 2000) . The goal of this work is to develop a method for summarising time-series data in order to provide continuous feedback to students across the entire semester. As a case study, we took a module i... | 0 |
The growing number of electronically available knowledge sources (KSs) emphasizes the importance of developing flexible and efficient tools for automatic knowledge acquisition and structuring in terms of knowledge integration. Different text and literature mining techniques have been developed recently in order to faci... | 0 |
Implicit discourse relations hold between adjacent sentences in the same paragraph, and are not signaled by any of the common explicit discourse connectives such as because, however, meanwhile, etc. Consider the two examples below, drawn from the Penn Discourse Treebank (PDTB) (Prasad et al., 2008) , of a causal and a ... | 0 |
Commonsense validation and explanation is a critical area in natural language understanding. Recent research advances (Yang et al., 2019; Devlin et al., 2018; pushed the bar in this area to a new height. SemEval 2020 Task 4 (Wang et al., 2020) is focused on this area. It has 3 subtasks. Subtask A is focused on commonse... | 0 |
Sequence tagging algorithms including HMMs (Rabiner, 1989 ), CRFs (Lafferty et al., 2001) , and Collins's perceptron (Collins, 2002) have been widely employed in NLP applications. Sequential decoding, which finds the best tag sequences for given inputs, is an important part of the sequential tagging framework. Traditio... | 0 |
The paper describes a computationally efficient dependency parsing algorithm. It has been developed for language engineering applications to precess raw text corpora on the syntactic level. Since our primary concern was the efficiency, we have considered a limited coverage of the syntactic constructions; hence disconti... | 0 |
Word sense ambiguity poses significant obstacles to accurate and efficient information extraction and automatic translation. Successful disambiguation of polysemous words in NLP applications depends on determining an appropriate level of granularity of sense distinctions, perhaps more so for distinguishing between mult... | 0 |
Bilingual lexicons serve as an indispensable source of knowledge for various cross-lingual tasks such as cross-lingual information retrieval (Lavrenko et al., 2002; Levow et al., 2005) or statistical machine translation (Och and Ney, 2003) . Additionally, they are a crucial component in cross-lingual knowledge transfer... | 0 |
The field of natural language processing (NLP) is currently in upheaval. A reason for this is the success story of deep learning, which has led to ever better reported performances across many different NLP tasks, sometimes exceeding the scores achieved by humans. These fanfares of victory are echoed by isolated voices... | 0 |
There is a big gap between the summaries produced by current automatic summarizers and the abstracts written by human professionals. Certainly one factor contributing to this gap is that automatic systems can not always correctly identify the important topics of an article. Another factor, however, which has received l... | 0 |
The Simple English Wikipedia 1 is an effort to make information in Wikipedia 2 accessible for less competent readers of English by using simple words and grammar. Examples of intended users include children and readers with special needs, such as users with learning disabilities and learners of English as a second lang... | 0 |
Recently, many phenomena appeared and spread in the Internet, especially with the huge propagation of information and the growth of social networks. Some of these phenomena are fake news, rumors and misinformation. In general, the detection of these phenomena is crucial since in many situations they expose the people t... | 0 |
Automatic algorithms are starting to generate interesting, creative text, as evidenced by recent distinguishability tests that ask whether a given story, poem, or song was written by a human or a computer. 1 In this paper, we describe Hafez, a program that generates any number of distinct poems on a user-supplied topic... | 0 |
The development of the Transformer (Vaswani et al., 2017 ) -a multi-headed attention architecture with high capacity -caused a breakthrough in the pre-training of contextualized representations for text (Radford et al., 2018; Devlin et al., 2019) . This architecture can internalize large amounts of information from mas... | 0 |
Natural Language Inference (NLI) is the task of determining whether a given hypothesis is true (entailment), false (contradiction) or undetermined (neutral) by inferring a given premise. The Stanford Natural Language Inference (SNLI) corpus is a well-known dataset and serves as a benchmark for NLI system evaluations (B... | 0 |
It has been long observed that Latinate verbs in English are typically bad with verb-particle constructions (e.g., Whorf, 1956; Di Sciullo and Williams, 1987; Harley, 2008) , resultative constructions (Harley, 2008) , and double object constructions (Pinker, 1989; Pesetsky, 1995; Harley, 2008) , which are commonly foun... | 0 |
Visual Question Answering (VQA) was firstly introduced to bridge the gap between natural language processing and image understanding applications in the joint space of vision and language (Malinowski and Fritz, 2014) .Most VQA benchmarks compute a question representation using word embedding techniques and Recurrent Ne... | 0 |
In large-scale machine translation evaluations, phrase-based models generally outperform syntaxbased models 1 . Phrase-based models are effective because they capture the lexical dependencies between languages. However, these models, which are equivalent to finite-state machines (Kumar and Byrne, 2003) , are unable to ... | 0 |
N -gram models have long been the stronghold of statistical language modeling approaches. Within the n-gram paradigm, straightforward approaches for increasing accuracy include using larger training sets and augmenting the contextual information within the n-gram window. Incorporating syntactic features into the contex... | 0 |
Analysing claims shared on social media is of growing interest, from social/political sciences to Artificial Intelligence (AI). Such analyses are often performed with respect to a specific set of topics (e.g. "immigration" or "abortion") that allow carrying out targeted studies of trends, understanding/quantifying hidd... | 0 |
Dialogue acts are a key issue in pragmatics that has been traditionally tackled by artificial intelligence. Nevertheless, computer science has been more interested in the structure and the interaction of agents in conversation (Litman and Allen, 1990 ) rather than in single utterances. From that perspective, some autho... | 0 |
Discourse relations refer to the relations between units of text at document level. As a key for language processing, they are used in tasks such as automatic summerization, sentiment analysis and text coherence assessment Trivedi and Eisenstein, 2013; Yoshida et al., 2014) . While discourse-annotated English resources... | 0 |
In this paper, we present an approach for extracting the named entities (NE) of natural language inputs which uses the maximum entropy (ME) framework (Berger et al., 1996) . The objective can be described as follows. Given a natural input sequence ¤ ¦ ¥ § © ¤ § ¤ ¤ ¥ we choose the NE tag sequence ¥ § § ¥with the highes... | 0 |
Recently, Text-to-SQL has drawn a great deal of attention from the semantic parsing community (Berant et al., 2013; Cao et al., 2019 . The ability to query a database with natural language (NL) engages the majority of users, who are not familiar with SQL language, in visiting large databases. A number of neural approac... | 0 |
One of the consequences of the data explosion of the past twenty-five years is the likelihood that a large number of computer scientists and computing professionals will have the opportunity to develop analytical tools for processing large, structured datasets during their careers. This is of course especially true in ... | 0 |
Recently, compressive and abstractive summarization are attracting attention (e.g., Almeida and Martins (2013) , Qian and Liu (2013) , Yao et al. (2015) , Banerjee et al. (2015) , Bing et al. (2015) ). However, extractive summarization remains a primary research topic because the linguistic quality of the resultant sum... | 0 |
A significant problem for statistical machine translation in a low-resource setting is data sparsity caused by highly inflected languages. Languages such as Arabic and Turkish, for example, are rich with complex morphology. For statistical machine translation, this means much more parallel data is required in order to ... | 0 |
In the last decades, task-oriented dialogue systems with human-like communication capabilities have been widely deployed in applications with commercial value such as restaurant reservation (Henderson et al., 2019) and online shopping (Yan et al., 2017) . As opposed to open-domain dialogue systems without a clear dialo... | 0 |
Named Entity Recognition (NER) aims at automatically identifying and classifying entities such as persons, places, organizations and values. This is a fundamental task in Information Extraction since, besides having several applications, other tasks such as relations and events extraction, question answering systems an... | 0 |
Morphological alterations of a search term have a negative impact on the recall performance of an information retrieval (IR) system (Choueka, 1990; Jäppinen and Niemistö, 1988; Kraaij and Pohlmann, 1996) , since they preclude a direct match between the search term proper and its morphological variants in the documents ... | 0 |
Assessment is a key component of the teaching and learning process. The templates provided by most Computer-Aided Assessment Systems are multiple-choice questions, true/false questions and matching questions. Only basic support around the management of open-ended questions (short answer questions and essays) is offered... | 0 |
.Duq to. its central role in natural lan-uage and .its mtm,mmg properties, relerence and an@]'-~or resolutton has been a central topic for NLP research. Given the intensive attentkm devoted to this subject, .it can however be said that sentential anaphor processing has been quite overlooked, when conmared to the amount... | 0 |
Word embeddings learned from unlabeled corpora are one of the cornerstones of modern natural language processing. They offer important advantages over their sparse counterparts, allowing efficient computation and capturing a surprising amount of lexical information about words based solely on usage data.Since precise w... | 0 |
In this paper, we present a GOLD standard of part-of-speech-tagged transcripts of spoken German. It comes with guidelines for the manual annotation of transcripts of spoken data and an extended version of the STTS (Stuttgart Tübingen Tagset) which accounts for phenomena typically found in spontaneous spoken German. The... | 0 |
Named Entity Recognition (NER) is a widely studied task of Natural Language Processing. Recent leading architectures achieved impressive performances, especially in formal contexts (like news articles, etc.) and for commonly worked named entity types (like Person, Organization, etc.) . In Multilingual Complex Named Ent... | 0 |
Fully automated machine translation of unconstrained texts is beyond the state of the art today. The need for mechanizing the translation process is, however, very urgent. It is desirable, therefore, to seek ways of both speeding up the process of translating texts and making it less expensive. In this paper we describ... | 0 |
Most of the world's languages are dying out and have little recorded data or linguistic documentation (Austin and Sallabank, 2011) . It is important to adequately document languages while they are alive so that they may be investigated in the future. Language documentation traditionally involves one-onone elicitation o... | 0 |
Dependency parsing is an approach to syntactic analysis inspired by dependency grammar. In recent years, interest in this approach has surged due to its usefulness in such applications as machine translation (Nakazawa et al., 2006) , information extraction (Culotta and Sorensen, 2004) .Graph-based parsing models (McDon... | 0 |
Active learning (AL), also called query learning and selective sampling, is an approach to reduce the costs of creating training data that has received considerable interest (e.g., (Argamon-Engelson and Dagan, 1999; Baldridge and Osborne, 2008; Bloodgood and Vijay-Shanker, 2009b; Bloodgood and Callison-Burch, 2010; Hac... | 0 |
Since there is an ongoing shift towards computer based studies in the humanities new challenges in maintaining and analysing electronic resources arise. This is all the more because research groups are often distributed over several institutes and universities. Thus, the ability to collaboratively work on shared resour... | 0 |
Recent research has achieved impressive results in zero-shot cross-lingual transfer based on multilingual pre-training (Devlin et al., 2019; Conneau and Lample, 2019) or monolingual transfer of embeddings (Artetxe et al., 2020) . However, these methods require large amounts of unlabeled data in the target language (Lau... | 0 |
We examine Machine Teaching (MT), an understudied interactive machine learning (iML) method under controlled simulation for the task of textbased emotion prediction (Liu et al., 2003; Aman and Szpakowicz, 2007; Alm, 2010; Bellegarda, 2013; Calvo and Mac Kim, 2013; Mohammad and Alm, 2015) . This problem intersects with ... | 0 |
To train Natural Language Generation (NLG) systems, various input-text corpora have been developed which associate (numerical, formal, linguistic) input with text. As discussed in detail in Sec-tion 2, these corpora can be classified into three main types namely, (i) domain specific corpora, (ii) benchmarks constructed... | 0 |
This research addresses an ethical consideration for Natural Language Generation, namely, plagiarism. The Oxford English Dictionary defines original (adjective) as "present or existing from the beginning; first or earliest" and "created directly and personally by a particular artist; not a copy or imitation". But, if w... | 0 |
Despite the high quality reached nowadays by neural machine translation (NMT), its output is often still not adequate for many specific domains handled daily by the translation industry. While NMT has shown to benefit from the availability of in-domain parallel or monolingual data to learn domain specific terms (Faraji... | 0 |
Despite the recent advancements in assigning attribute profiles to dialogue agents (Qian et al., 2018; , maintaining a consistent profile is still challenging for an open-domain dialogue agent. Existing works mainly emphasize the incorporation of attribute information in the generated responses (Wolf et al., 2019; Zhen... | 0 |
Recently, the need for extracting temporal information from text is motivated rapidly by many NLP tasks such as: question answering (QA), information extraction (IE), etc. Along with the TimeBank 1 (Pustejovsky et al., 2003) and other temporal information annotated corpora, a series of temporal evaluation challenges (T... | 0 |
This paper shows our proposed system for the SemEval-2020 task 11: Detection of Propaganda Techniques in News Articles (Da San Martino et al., 2020) . The goal of the task was to design a model to detect and classify propaganda. To this end, there are two subtasks: span identification (SI) for predicting propaganda spa... | 0 |
The research concerned with automatically reducing the complexity of texts is called Automatic Text Simplification (ATS). Automatic text simplification was first proposed as a pre-processing step prior to other natural language processing tasks, such as machine translation or text summarisation.The assumption was that ... | 0 |
Data-driven task-oriented dialogue systems have been a focal point in both academic and industry research recently. Generally, the first step of building a dialogue system is to clarify what users are allowed to do. Then developers can collect data to train dialogue models to support the defined capabilities. Such syst... | 0 |
In many constituency treebanks, the syntactic annotation takes the form of Context-Free Grammar (CFG) derivation trees, i.e., of trees with no crossing branches. Discontinuous structures (Huck and Ojeda, 1987 ) cannot be modeled with CFG and are therefore handled by an additional mechanism in such an annotation. In the... | 0 |
Quantification occurs in every sentence of written text or spoken discourse. This is because the application of a predicate to one or more sets of objects gives rise to questions of relative scope, of cardinality, and of the distribution (or 'distributivity') of the predicate over the sets of arguments. Dealing with th... | 0 |
Much recent statistical information extraction research has applied graphical models to extract information from one particular document after training on a large corpus of annotated data (Leek, 1997; Freitag and McCallum, 1999) . 1 Such systems are widely applicable, yet there remain many information extraction tasks ... | 0 |
Text classification has been used for numerous applications including sentiment analysis (Hemmatian and Sohrabi, 2019), information retrieval (Aggarwal and Zhai, 2012), and language identification (Jauhiainen et al., 2019) . When presented with a large number of labeled documents, common text classification models demo... | 0 |
Text classification is a fundamental NLP task with numerous real-world applications such as topic recognition (Tang et al., 2015; Yang et al., 2016) , sentiment analysis (Pang and Lee, 2005; Yang et al., 2016) , and question answering (Chen et al., 2015; Kumar et al., 2015) . Classification also appears as a sub-task f... | 0 |
Research on domain-specific automatic term recognition (ATR) and on general-language collocation extraction (CE) has gone mostly separate ways in the last decade although their underlying procedures and goals turn out to be rather similar. In both cases, linguistic filters (POS taggers, phrase chunkers, (shallow) parse... | 0 |
In the 2012 IWSLT Evaluation Campaign [1] , we participated in the TED task for the Arabic-English and Turkish-English language pairs. Our major focus this year was improving the word alignment.Maximum-likelihood (ML) word alignments obtained using GIZA++ [2] can exhibit overfitting, e.g., rare words can have excessive... | 0 |
Various studies have raised the question of which factors play a role in the choice of referring expressions. One of the main ideas in this tradition (henceforth, the linguistic tradition) is that there is a direct relationship between the "prominence" (in a broad sense) of a referent at a given point in the discourse,... | 0 |
A robust understanding of semantic meaning, despite variances in sentence expression, is an integral part of natural language processing (NLP) tasks. However, many existing NLP models exhibit shortcomings in understanding real-world variations in natural language. These models are often overreliant on learned spurious ... | 0 |
As language technologies emerge, we must assess their applicability to various tasks and determine how they can be used in a complementary fashion. In this paper, we will focus on the joint use of information extraction and machine translation. We will present empirical data which demonstrates the effectiveness of this... | 0 |
A high-quality Statistical Machine Translation (SMT) system can only be built with large quantities of parallel texts. Moreover, systems specialized in specific domains require in-domain training data. A well-known problem of SMT systems is that existing parallel corpora cover a small percentage of the possible languag... | 0 |
Large-scale lexical semantic resources that provide relational information about words have recently received much focus in the field of Natural Language Processing (NLP). In particular, data-driven models for lexical semantics require the creation of broad-coverage, hand-annotated corpora with predicateargument inform... | 0 |
The rapid global proliferation of Internet applications has been showing no deceleration since the new millennium. For example, in commerce more and more physical customer services/call centers are replaced by Internet solutions, e.g. via MSN, ICQ, etc. Network informal language (NIL) is actively used in these applicat... | 0 |
Detecting offensive language or hate speech on social media has gained a lot of interest recently. Use of offensive language and hate speech on social media can be an indication of hate crimes, toxic environment or level of antagonism against individuals or particular groups. Detecting offensive language and hate speec... | 0 |
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