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In distantly-supervised information extraction (IE), a knowledge base (KB) of relation or concept instances is used to train an IE system. For instance, a set of facts like adverse-EffectOf(meloxicam, stomachBleeding), interacts-With(meloxicam, ibuprofen), might be used to train an IE system that extracts these relatio... | 0 |
Information Extraction (IE) systems can identify 'facts' (entities, relations and events) of particular types within individual documents, and so can unleash the knowledge embedded in texts for many domains, such as military monitoring, daily news, financial analysis and biomedical reports. However, most current IE sys... | 0 |
There is only a small set 1 of prepositions in English that function as spatial and temporal signals. Prepositions such as at, in, during, by, since, from, to, through, till, before, and after in English trigger various temporal relations over events, times or locations.ISO-TimeML (2012) puts these prepositions used as... | 0 |
SemEval-2017 Task 5 is Fine-Grained Sentiment Analysis on Financial Microblogs and News (Cortis et al., 2017) , focusing on identifying positive (bullish; believing that the stock price will increase) and negative (bearish; believing that the stock price will decline) sentiment associated with stocks and companies from... | 0 |
There is growing interest and activity in applying computing technology to unearth the knowledge content of India's heritage literature embedded in Indic languages due to its perceived value to modern society. This has led to several research efforts to produce analysis tools for Indic language content at various level... | 0 |
In recent years the improvements in quality of word embeddings led to significant improvements in many natural language processing (NLP) tasks, e.g. sentiment analysis (Maas et al., 2011) , named entity recognition (Lample et al., 2016) , or machine translation (Zou et al., 2013) . New models for word embeddings and im... | 0 |
Pronunciation dictionaries are a crucial component of speech recognition and speech synthesis systems, as they form the link between the acoustic and symbolic level of automatic speech and language processing. Typically, each entry in a lexicon is assigned a phonetic transcription that represents its canonical form, i.... | 0 |
The way we see the world can be expressed using a myriad of words offered by the vocabulary of the language we speak in. Language vocabularies leave us with an infinity of choices to make and this is largely due to the fact that we have different words with similar meanings. While enriching our views of the world, this... | 0 |
Building chatbot engines that can interact with humans with natural language is one of the most challenging problems in artificial intelligence. Along with the explosive growth of social media, like community question answering (CQA) websites (e.g., Yahoo Answers and WikiAnswers) and social media websites (e.g., Twitte... | 0 |
The ACL Anthology is one of the most successful initiatives of the ACL. It was initiated by Steven Bird and is now maintained by Min Yen Kan. It includes all papers published by ACL and related organizations as well as the Computational Linguistics journal over a period of four decades. It is available at http://www.ac... | 0 |
In recent years, there has been a considerable amount of research into attempting to represent contexts longer than single words with fixedlength vectors. These representations typically tend to focus on attempting to represent sentences, although phrase-and paragraph-centric mechanisms do exist. These have moved well ... | 0 |
Large language models (LMs) learn social biases present in the world, and the increased use of these systems across different contexts increases the cases where these biases can lead to harm. LMs have been found to reproduce social biases in downstream tasks such as language generation (Sheng et al., 2019) and corefere... | 0 |
Building task-oriented dialogue systems using a conventional pipeline approach, where modules are optimized separately, increases the fine control for dialogue management, but it does not necessarily improve overall performance (Madotto et al., 2018; Liu and Lane, 2018) . In contrast, end-to-end neural models employ a ... | 0 |
There is a growing literature on using webacquired data for constructing various types of language resources, including monolingual and parallel corpora. As shown in, among others, Pecina et al. (2014) and Rubino et al. (2015) , such resources can be exploited in training generic or domainspecific machine translation s... | 0 |
Out-of-vocabulary (oov) words or phrases still remain a challenge in statistical machine translation. SMT systems usually copy unknown words verbatim to the target language output. Although this is helpful in translating a small fraction of oovs such as named entities for languages with same writing systems, it harms t... | 0 |
Compound word formation in Sanskrit is governed by a set of deterministic rules following a well-defined structure described in Pān . ini's As . t.ā dhyāyī, a seminal work on Sanskrit grammar. The process of merging two or more morphemes to form a word in Sanskrit is called Sandhi and the process of breaking a compound... | 0 |
Statistical Machine Translation(SMT) is currently the state of the art solution to the machine translation. Phrase based SMT is also among the top performing approaches available as of today. This approach is a purely lexical approach, using surface forms of the words in the parallel corpus to generate the translations... | 0 |
Aspect term extraction (ATE), which aims to identify and extract the aspects on which users express their sentiments (Hu and Liu, 2004; Liu, 2012) , is a fundamental task in aspect-level sentiment analysis. For example, in the sentence of "The screen is very large and crystal clear with amazing colors and resolution", ... | 0 |
While large transformer-based autoregressive language models trained on massive amounts of data found on the internet exhibit exceptional capabilities to generate natural language text, effective methods for generating text that satisfy global constraints and possess holistic desired attributes remains an active area o... | 0 |
The n-gram model has been widely applied in many applications such as speech recognition, machine translation, and Asian language text input [Jelinek, 1990; Brown et al., 1990; Gao et al., 2002] . It is a stochastic model, which predicts the next word (predicted word) given the previous n-1 words (conditional words) in... | 0 |
Coherent discourse is characterized by local properties that are crucial for comprehension. In fact, a long line of linguistics and computational linguistics tradition has proposed that several levels of structure contribute to the creation of coherent discourse. Among these, the attentional structure (Grosz et al., 19... | 0 |
Distributional semantics embraces a set of methods that decipher the meaning of linguistic entities using their usages in large corpora (Lenci, 2008) . In these methods, the distributional properties of linguistic entities in various contexts, which are collected from their observations in corpora, are compared to quan... | 0 |
In recent years, e-commerce is widely used throughout the world and it enables people to purchase products from foreign countries.However, sometimes it is not easy for foreign buyers to find the products they want because of the language difference. In our case, the alphabetic queries that are input by non-Japanese buy... | 0 |
The Never-Ending Language Learner (NELL) (Carlson et al., 2010b) ) is a computer system that learns continuously to extract facts from the web. NELL is given as input an initial ontology that specifies the semantic categories (e.g. city, company, sportsTeam) and semantic relations (e.g. hasOf-ficesIn(company,city), tea... | 0 |
Dependency grammar has a long tradition in syntactic theory, dating back to at least Tesnière's work from the thirties. Recently, it has gained renewed attention as empirical methods in parsing have emphasized the importance of relations between words (see, e.g., (Collins, 1997)) , which is what dependency grammars mod... | 0 |
Similarly to many other NLP tasks, performance of automatic document summarization has been improving with the recent rise of neural network methods. While deep neural network models can leverage large datasets, only a few moderately-sized datasets are available for document summarization when compared to, e.g., machin... | 0 |
The main purpose of the GermaNet Editing Tool GernEdiT tool is to support lexicographers in accessing, modifying, and extending the Ger-maNet data (Kunze and Lemnitzer, 2002; Henrich and Hinrichs, 2010) in an easy and adaptive way and to aid in the navigation through the GermaNet word class hierarchies, so as to find t... | 0 |
As a result of open access policy (European Commission, 2011) adopted by Galleries, Libraries, Archives and Museums (GLAMs), a huge collection of cultural and historical resources is now available on the internet to promote access. Many GLAMs started to publish digital resources and the associated metadata to support e... | 0 |
Deep processing is the process of applying rich linguistic resources within NLP tasks, to arrive at a detailed (=deep) syntactic and semantic analysis of the data. It is conventionally driven by deep grammars, which encode linguistically-motivated predictions of language behaviour, are usually capable of both parsing a... | 0 |
Automatic medical code assignment is a routine healthcare task for medical information management and clinical decision support. The International Classification of Diseases (ICD) coding system, maintained by the World Health Organization (WHO), is widely used among various coding systems. Thus, the medical code assign... | 0 |
News articles are a useful target for opinion mining as they discuss salient opinions by newsworthy people. Rather than asserting what a person's opinion is, journalists typically provide evidence by using reported speech, and in particular, direct quotes. We focus on direct quotes as expressions of opinion, as they ca... | 0 |
Urdu is an Indo-Aryan language that is the national language and lingua franca of Pakistan, and an official language of multiple states of India. There are 109 million speakers of Urdu in Pakistan and 51 million speakers in India. Urdu is also widely spoken across the rest of the world, with more than 163 million total... | 0 |
In the machine translation MT literature, it has often been argued that translations of natural language texts are valid if and only if the source language text and the target language text have the same meaning cf. e.g. Nagao, 1989 . If we assume that MT systems produce meaningful translations to a certain extent, we ... | 0 |
Conversational agents are of growing importance in facilitating smooth interaction between humans and their electronic devices, yet conventional dialog systems continue to face major challenges in the form of robustness, scalability and domain adaptation. Attention has thus turned to learning conversational patterns fr... | 0 |
Japanese predicate argument structure analysis (PASA) examines semantic structures between the predicate and its arguments in a text. The identification of the argument structure such as "who did what to whom?" is useful for natural language processing that requires deep analysis of complicated sentences such as machin... | 0 |
Nowadays wikipedia and large scale knowledge bases such as YAGO (Suchanek et al., 2007) , freebase (Bollacker et al., 2008) and DBpedia (Lehmann et al., 2015) are available for supporting what-knowledge. Users can find facts about entities and know their relationships from such a kind of knowledge bases. How-knowledge ... | 0 |
As an alternative to requiring substantial supervised relation training data (e.g. the ~300k words of detailed, exhaustive annotation in Automatic Content Extraction (ACE) evaluations 1 ) many have explored bootstrapping relation extraction from a few (~20) seed instances of a relation. Key to such approaches is a larg... | 0 |
Statistical machine translation (SMT) systems are based on two types of resources: monolingual data to build a language model (LM) and bilingual data -also called bitexts -to train the translation model (TM). The parallel data often comes from different sources, e.g. Europarl, UN, in-domain data in limited amounts, dat... | 0 |
Twitter is an online social networking and microblogging service that enables users to send and read short 140-character messages called "tweets". As of the first quarter of 2015, the microblogging service averaged at 236 million monthly active users. Worldwide over 350 billion SMS text messages are exchanged across th... | 0 |
Human beings have constantly tried to create an identity for themselves, and with the world becoming increasingly progressive, they have more freedom of choice in many spheres of life, including gender expressions and sexuality. (Cederved et al., 2021) However, the understanding of these concepts continues to gradually... | 0 |
Les hallucinations auditives verbales (HAVs) sont un des symptômes les plus invalidants de la schizophrénie, touchant entre 50% et 80% des patients. Elles ont été définies comme «a sensory experience which occurs in the absence of corresponding external stimulation of the relevant sensory organ, has a sufficient sense ... | 0 |
The problem of mapping a natural language utterance into an executable SQL query in the crossdatabase and context-dependent setting has attracted considerable attention due to its wide range of applications (Wang et al., 2020b; Zhong et al., 2020) . This problem is notoriously challenging, due to the complex contextual... | 0 |
A translation lexicon is an important component of multilingual processing applications such as machine translation systems (Brown et al., 1990; Al-Onaizan et al., 1999) and multilingual information retrieval systems (Sheridan and Ballerini, 1996; CLE, 2005) . A translation lexicon can also facilitate cross-lingual res... | 0 |
Recently, there has been some interest in the implementation of grammatical theories based on the principles and parameters approach (Correa [3] , Dorr [4] , Johnson [5] , Kolb & Thiersch [6] , and Stabler [10] ). In this framework, a fixed set of universal principles parameterized according to particular languages int... | 0 |
Phrase-based Statistical Machine Translation has proven to be a robust and effective approach to machine translation, providing good performance without the need for explicit linguistic information. Phrase-based SMT systems, however, have limited capabilities in dealing with long distance phenomena, since they rely on ... | 0 |
Natural language processing (NLP) datasets are plagued with artifacts and biases, which allow models to perform tasks without learning the desired underlying language capabilities. For instance, in natural language inference (NLI) datasets, models can predict an entailment relationship y from the hypothesis text H alon... | 0 |
One of the tasks in educational NLP systems is providing feedback to students in the context of exam questions, homework or intelligent tutoring. Much previous work has been devoted to the automated scoring of essays (Attali and Burstein, 2006; Shermis and Burstein, 2013) , error detection and correction (Leacock et al... | 0 |
The resource-based approach to semantic composition in Lexical-Functional Grammar (LFG) obtains the interpretation for a phrase via a logical deduction, beginning with the interpretations of its parts as premises (Dalrymple et al., 1993a) .The resource-sensitive system of linear logic is used to compute meanings in acc... | 0 |
The GEC task has attracted wide interest in recent years. The goal of GEC is to detect and correct errors in essays made by English as a Second Language (ESL) learners. Since the end of both CoNLL2013 (Ng et al., 2013 and CoNLL2014 (Ng et al., 2014 , many GEC researchers have used the two test sets as benchmark evaluat... | 0 |
Attention mechanisms have been ubiquitous in neural machine translation (NMT) (Bahdanau et al., 2015; Vaswani et al., 2017) . It dynamically encodes source-side information by inducing a conditional distribution over inputs, where the ones that are most relevant to the current translation are expected to receive more a... | 0 |
Recently, the topic of exploring semantic representation in human brain has attracted the attention of researchers from both neuroscience and computational linguistics fields. In these studies, concepts are represented in terms of neural activation patterns in the brain that can be recorded by functional magnetic reson... | 0 |
Sanskrit is an Indo-Aryan language that served as lingua franca for the religious, scientific and literary communities of ancient India. Text production in Sanskrit started in the 2. millenium BCE and has continued until today. 1 A 19th century cataloguing project recorded more than 40,000 Sanskrit texts known at that ... | 0 |
Sentiment analysis becomes more and more important as various user generated content(UGC) appears on the web, such as product reviews and personal blogs. Unsupervised sentiment classification has a great advantage that it does not need a large expensive labeled corpus but only a user defined sentiment dictionary. Howev... | 0 |
Multimodal data fusion is a desirable method for many machine learning tasks where information is available from multiple source modalities, typically achieving better predictions through integration of information from different modalities. Multimodal integration can handle missing data from one or more modalities. Si... | 0 |
Entity Linking (EL) is an Information Extraction task whose goal is to identify mentions of entities in a text and to link each mention to an unambiguous identifier in a Knowledge Base (KB) such as Wikipedia, BabelNet (Moro et al., 2014) , DBpedia (Lehmann et al., 2015) , Freebase (Bollacker et al., 2008) , Wikidata (V... | 0 |
Information extraction subsumes a broad range of tasks, including the extraction of entities, relations and events from various text sources, such as newswire documents and broadcast transcripts. One such task, relation detection, finds instances of predefined relations between pairs of entities, such as a Located-In r... | 0 |
Recently, with the emergence of large structured knowledge bases (KBs) like DBpedia (Auer et al., 2007) , Freebase (Bollacker et al., 2008) and Yago (Suchanek et al., 2007) , increasing research efforts on automatically answering natural language questions has shifted from using text corpora only to large scale structu... | 0 |
Any natural language processing system needs both knowledge about words and knowledge about the world. Many natural language systems divide these two kinds of knowledge into two knowledge bases, which we call the lexicon and the encyclopedia for the purposes of this discussion. We argue that the distinction between the... | 0 |
Neural named entity recognition (NER) has become a mainstream approach due to its superior performance (Huang et al., 2015; Lample et al., 2016; Ma and Hovy, 2016; Chiu and Nichols, 2016; Akbik et al., 2018) . However, neural NER typically requires a large amount of manually labeled training data, which are not always ... | 0 |
Nowadays, text analysis and semantic similarity are subject to a lot of research and experiments due to the growth of social media influence, the increasing usage of forums for finding a solution of common known problems and the Web upgrowth. As beginners in the computational linguistics field, we were very interested ... | 0 |
There have been several successful attempts in recent years to employ automatically parsed data in semi-and unsupervised approaches to parser domain adaptation (McClosky et al., 2006b; Reichart and Rappaport, 2007; Huang and Harper, 2009; Petrov et al., 2010) . We turn our attention to adapting a Wall-Street-Journal-tr... | 0 |
Though the goal of machine translation is to generate semantically accurate translations from one language to another, there are other factors which affect whether a translation is "good". One often-neglected factor is the reading level of the translation-different contexts require different reading levels. When transl... | 0 |
Sentiment Analysis has become a very active area of research during the last decade. The reason behind this rising popularity is twofold. First, sentiment analysis has a great number of applications varying from academia to commercial domains such as customer support, brand management, social media marketing e.t.c. Sec... | 0 |
In this paper we discuss ROSE, an interactive approach to robust interpretation developed in the context of the JANUS speech-to-speech translation system (Lavie et al., 1996) . Previous interactive approaches to robust interpretation have either required excessive amounts of interaction (Ros4 and Waibel, 1994) , depend... | 0 |
While there have been many advances in the field of machine translation, it is widely acknowledged that current systems do not yet produce satisfactory results. At the same time, many researchers also recognize that no single paradigm solves all of the problems necessary to achieve high coverage while maintaining fluen... | 0 |
An a,lluring a,spect of the staMstica,1 a,pproa,ch to ins,chine tra,nsla,tion rejuvena.ted by Brown, et al., [_1] is the systems.tic framework it provides for a.tta.cking the problem of lexicM dis~tmbigua.tion. For example, the system they describe tra,ns]a.tes th.e French sentence Je vais prendre la ddeision a,s [ wil... | 0 |
We address the problem of revising the lead sentence in a broadcast news text to increase the amount of background information in the lead. This is one of the draft and revision approaches to summarization, which has received keen attention in the research community. Unlike many other methods that directly utilize noun... | 0 |
Open-retrieval 3 question answering (QA) is a task of answering questions in diverse domains given large-scale document collections such as Wikipedia . Despite the rapid progress in this area Karpukhin et al., 2020; Lewis et al., 2020b) , the systems have primarily been evaluated in English, yet openretrieval QA in non... | 0 |
Machine learning approaches have been shown to be capable of making accurate predictions in many well-known problem domains with an abundance of training data. This heavy reliance on the availability of the data, however, may hamper the application of machine learning approaches to resourcelimited problem domains, wher... | 0 |
Our submitted system consists of an end to end speech recognition model and a neural machine translation model which follows the traditional pipeline framework in simultaneous translation task. The system input is Chinese audio file and the output is English translation text. A temporary Streaming transcription is obta... | 0 |
The present paper presents ideas concerning a methodology of the 'semantics in computational linguistics' (COLsemantics).There is the following hypothesis underlying:In the field of COL-semantics algorithms and computer programs are developed which deliver structures of linguistic analysis and representation that can b... | 0 |
As the means of natural language processing axe gradually reaching a stage where the realisation of large-scale projects like EUROTRA becomes more and more feasible, the demand for lexical databases increases. Unfortunately, this is not a demand which is easy to meet, because lexical databases are exceedingly expensive... | 0 |
As a cultural and social construction, gender refers to gender roles distinguishing masculine behaviors from feminine behaviors. (Hu, 2018:118) Since Translation 1 is in essence a process of bilingual transformation and information processing, its process and production are supposed to be influenced by gender. Corpus-b... | 0 |
Ce travail s'inscrit dans le cadre général du développement de ressources lexicales pouvant être utilisées dans différentes applications du TAL. L'exemple qui nous a servi de tremplin est le lexique Verbaction 1 qui contient 6 471 couples verbe:nom, tels que le nom est morphologiquement apparenté au verbe et qu'il déno... | 0 |
In recent years, hierarchical methods have been successfully applied to Statistical Machine Translation (Graehl and Knight, 2004; Chiang, 2005; Ding and Palmer, 2005; Quirk et al., 2005) . In some language pairs, i.e. Chinese-to-English translation, state-ofthe-art hierarchical systems show significant advantage over p... | 0 |
The background of this this paper is in two types of modeling of information flow in news stream, namely, burst analysis and topic modeling. Both types of modeling, to some extent, aim at aggregating information and reducing redundancy within the information flow in news stream.First, when one wants to detect a kind of... | 0 |
The proliferation of Web 2.0 has enabled ready access to large amounts of community created content, such as status messages, blogs, wikis, and reviews. These form an important source of knowledge in our day to day decision making, such as deciding which restaurant to try, or which movie to watch, or which city to visi... | 0 |
The Message Understanding Conferences MUCs have been held with the goal of qualitatively evaluating message understanding systems. While the MUCs held thus far have been quite successful at providing such an evaluation, very little work has been done in analyzing the di culty of understanding a text in a particular dom... | 0 |
This paper demonstrates a multimodal interface for asking questions and retrieving a set of likely answers. Such an interface is particularly appropriate for mobile networked devices with screens that are too small to display general Web pages and documents. Palm and Pocket PC devices, whose screens commonly display 10... | 0 |
Parsing algorithms for contex-free grammars (CFGs) are generally recognized as the backbone of virtually all approaches to parsing natural-language. Even in systems that use a grammar formalism more complex than CFGs (e.g., unification grammar), the parsing method is usually an extension of one of the well-known CFG pa... | 0 |
A word n-gram is a continuous sequence of n words from a corpus of texts or speech. Word n-gram language models are widely used in Natural Language Processing (NLP), such as speech recognition, machine translation, and information retrieval. The effectiveness of a word n-gram language model is highly dependent on the s... | 0 |
Existence of good knowledge graphs is essential for question answering system. Due to inefficiency of manually adding triples to a knowledge graph, researches about extracting triples from raw text have been being conducted. Relation Extraction (RE) is a task to extract relational facts from unstructured text in triple... | 0 |
Tasks in computational linguistics (CL) normally focus on the content of a document while paying little attention to the context in which it was produced. The work described in this paper considers the importance of temporal context. We show that knowing one small piece of information-a document's publication date-can ... | 0 |
A growing amount of biomedical data is continuously being produced, resulting largely from the widespread application of highthroughput techniques, such as gene and protein analysis. This growth is accompanied by a corresponding increase of textual information, in the form of articles, books and technical reports. In o... | 0 |
There are two facts that conspire to make tile treatment of disjunction an important consideration when building a natural language processing (NLP) system. The first fact is that natural languages are full of ambiguities, and in a grammar many of these ambiguities are described by disjunctions. The second fact is that... | 0 |
German language has different national and regional variants. Standard national varieties spoken in Germany, Austria, and Switzerland co-exist with a number of dialects spoken in everyday communication. The German Dialect Identification task is concerned with identifying the specific German dialect in a written form. T... | 0 |
Constituent parsing is one of the most fundamental tasks in Natural Language Processing (NLP). It seeks to uncover the underlying recursive phrase structure of sentences. Most of the state-of-theart parsers are based on the PCFG paradigm and chart-based decoding algorithms (Collins, 1999; Charniak, 2000; Petrov et al.,... | 0 |
Machine translation (MT) has achieved huge advances in the past few years (Bahdanau et al., 2015; Gehring et al., 2017; Vaswani et al., 2017 Vaswani et al., , 2018 . However, the need for a large amount of manual parallel data obstructs its performance under low-resource conditions. Building an effective model on low r... | 0 |
At least three learning paradigms have been applied to the task of extracting relational facts from text (for example, learning that a person is employed by a particular organization, or that a geographic entity is located in a particular region).In supervised approaches, sentences in a corpus are first hand-labeled fo... | 0 |
In this paper, we present a richly annotated and genrediversified language resource, the Prague Dependency Treebank-Consolidated version 1.0 (PDT-C in the sequel). PDT-C 1 is a treebank from the family of PDT-style corpora developed in Prague (for more information, see Hajič et al. (2017) ). The main features of this a... | 0 |
Author profiling and author identification are two tasks in the context of the automatic derivation of author-related information from textual material. In the case of author profiling, demographic author information such as gender or age is to be derived; in the case of author identification, the goal is to predict th... | 0 |
The vast number of patent documents submitted to patent offices worldwide calls for the need of advanced patent search technologies, which could deal effectively with the complexity and the unique characteristics of patents. The majority of existing patent retrieval techniques and search engines rely upon text, given t... | 0 |
Spelling errors are common in practice and the errors will be enlarged in the downstream tasks. Therefore, Spelling correction is important to many NLP applications such as search optimization (Martins and Silva, 2004; Gao et al., 2010) , machine translation (Belinkov and Bisk, 2017) , part-ofspeech tagging (Van Rooy a... | 0 |
Maximum entropy modelling has been recently introduced to the NLP community and proved to be an expressive and powerful framework. The maximum entropy model is a model which fits a set of pre-defined constraints and assumes maximum ignorance about everything which is not subject to its constraints thus assigning such c... | 0 |
The CoNLL-SIGMOPRHON 2018 shared task consists of two subtasks out of which we participate only in the first subtask, which involves generating a target inflected form from a given lemma with its morphosyntactic descriptions (MSDs) provided as a set of features. For instance, the word thinking is the present continuous... | 0 |
Implicature is the term used in semantics and pragmatics to describe an inference that goes beyond the literal sense of what is said. Implicatures have received relatively limited attention in computational linguistics, since they are highly dependent on the communication context and on commonsense knowledge. However, ... | 0 |
Grammatical error correction (GEC) has been an active research area since a series of shared tasks was launched at CoNLL (Ng et al., 2013 . The GEC mainly constitutes a generative task, i.e., a task that produces a grammatically correct sentence from a given original sentence whereby multiple distinct outputs can be ju... | 0 |
It is quite common to dictate reports and leave the typing to typists -especially for the medical domain, where every consultation or treatment has to be documented. Automatic Speech Recognition (ASR) can support professional typists in their work by providing a transcript of what has been dictated. However, manual cor... | 0 |
The ability to automatically generate paraphrases (alternative phrasings of the same content) has been shown to be useful in many areas of Natural Language Processing such as question answering (Riezler et al., 2007) , semantic parsing (Berant and Liang, 2014) ), machine translation (Kauchak and Barzilay, 2006; Zhou et... | 0 |
The goal of Semantic Textual Similarity (STS) is to measure semantic similarity of two given text snippets. STS has been recently proposed by Agirre et al. (2012) as a pilot task, which has close relationship with both tasks of Textual Entailment and Paraphrase, but not equivalent with them and it is more directly appl... | 0 |
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