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Natural language processing allows us to build language models, and these models can be used to distinguish between languages. In the context of written text, such as newspaper articles or short stories, the author's style could be considered a distinct "language." Authorship attribution, also referred to as authorship... | 0 |
Research in recent years has moved to applying distributional semantic space models to tasks that deal in more complicated meaning structures like phrases and sentences. The underlying question in those applications is how to model compositionality, or the idea that the meaning of a larger linguistic unit is a function... | 0 |
Many popular applications (apps) on mobile devices are about language.They range from general-purpose translators to tourist phrase books, dictionaries, and language learning programs. Many of the apps are commercial and based on proprietary resources and software. The mobile APIs (both Android and iOS) make it easy to... | 0 |
Significant progress has been made in statistical machine translation (SMT) in recent years. Among all the proposed approaches, the phrasebased method (Koehn et al., 2003) has become the widely adopted one in SMT due to its capability of capturing local context information from adjacent words. There exists significant ... | 0 |
Many authors have developed dependency theories that cover cross-linguistically the most significant phenomena of natural language syntax: the approaches range from generative formalisms (Sgall et al. 1986) , to lexically-based descriptions (Mel'cuk 1988) , to hierarchical organizations of linguistic knowledge (Hudson ... | 0 |
Methods have been developed to efficiently obtain representations of words in R d that capture subtle semantics across the dimensions of the vectors (Collobert and Weston, 2008) . For instance, after sufficient training, relationships encoded in difference vectors can be uncovered with vector arithmetic: vec("king") -v... | 0 |
One significant weakness of conventional phrasebased (PB) models (Koehn et al., 2003) is that it only uses continuous phrases and thus cannot learn generalizations, such as French ne. . . pas to English not (Galley and Manning, 2010) . Although using tree structures is believed to be a promising way to solve this probl... | 0 |
Rule-based machine translation (RBMT) systems that employ a transfer-based translation approach, highly depend on the quality of their analysis phase as it provides the basis for its later processing phases, namely transfer and generation. Any parse failures encountered in the initial analysis phase will proliferate an... | 0 |
In recent years, large pre-trained language models (PLMs), such as T5 and GPT-3 (Brown et al., 2020) , have revolutionized the field of natural language processing (NLP), achieving remarkable performance on various downstream tasks (Qiu et al., 2020) . These PLMs have learned a substantial amount of in-depth knowledge ... | 0 |
Cet article présente les principes de fonctionnement et les intérêts de la plate-forme logicielle ProxiDocs dédiée à des analyses thématiques de corpus de textes. Sur le modèle de (Pichon et Sébillot, 1999) , nous entendons par thèmes, les sujets abordés dans un texte. Traiter la thématique d'un texte revient donc pour... | 0 |
Text simplification is the process of reducing the linguistic complexity of a text, while still retaining the original information content and meaning. Text Simplification is often thought of as consisting of two components -syntactic simplification and lexical simplification. While syntactic simplification aims at red... | 0 |
Complicated sentences impose difficulties on reading comprehension. For instance, a person in 5th grade can comprehend a comic book easily but will struggle to understand New York Times articles which require at least 12th grade average reading level (Flesch, 1981) . Complicated sentences also challenge natural languag... | 0 |
The task of multi-hop explanation generation has recently received interest as it could be a stepping-stone towards general multi-hop inference over language. Multi-hop reasoning requires algorithms to combine multiple sources of evidence. This becomes increasingly hard when the number of required facts for an inferenc... | 0 |
Advances in sensor and data storage technologies have rapidly increased the amount of data produced in various fields such as weather, finance, and sports. In order to address the information overload caused by the massive data, datato-text generation technology, which expresses the contents of data in natural language... | 0 |
Big data being a buzz word which has created an immense hype in the society, many analytical models are employed in order to repurpose those data and derive insights. With the advancements of distributed systems and theoretically cheap storage, there are less constraints to capture data as much as possible and store th... | 0 |
Recent work in Neural Machine Translation (NMT) relies on a sequence-to-sequence model with global attention (Sutskever et al., 2014; Bahdanau et al., 2014) , trained with maximum likelihood estimation (MLE). These models are typically trained by teacher forcing, in which the model makes each decision conditioned on th... | 0 |
Everyone has seen, experienced, and expressed patronizing and condescending language (PCL). Someone is patronizing or condescending when they communicate in a way that talks down to others, positions themselves in a superior position to the subjective group, or describes them in a charitable way in order to raise a fee... | 0 |
Domain adaptation is very important for information extraction (IE) systems. IE systems in the real world are often required to work for new domains and new tasks within a limited adaptation or tuning time. Thus, automatic learning of relation extraction rules for a new domain or a new task has been established as a re... | 0 |
Many NLP resources have been developed for processing Indian languages in the last decade. A major consortium of Indian language -Indian language MT system (ILMT) has been successfully carried out for 9 language pairs. These systems mainly follow a transfer based approach. MT system from English to various Indian langu... | 0 |
As Machine Translation (MT) becomes widely available for a large number of language pairs and the demand for faster and cheaper translations increases, its adoption is becoming more popular in the translation industry. However, it is well known that except in very narrow domains with dedicated MT systems, automatic tra... | 0 |
The typed-similarity dataset comprises pairs of Cultural Heritage items from Europeana 1 , a single access point to digitised versions of books, paintings, films, museum objects and archival records from institutions throughout Europe. Typically, the items comprise meta-data describing a cultural heritage item and, som... | 0 |
In several natural language processing tasks, such as automatic speech recognition and machine translation, state-of-the-art systems rely on the statistical approach.Statistical machine translation (SMT) is based on parametric models incorporating a large number of observations and probabilities estimated from monoling... | 0 |
Sentiment analysis and opinion mining has been an important sub-discipline in natural language processing, information retrieval and machine learning. Related techniques have many applications, such as product/travel/movie recommendation, automatic opinion poll, melancholia detection, etc., so not only researchers try ... | 0 |
In such pro-drop languages as Japanese, Chinese and Italian, pronouns are frequently omitted in text. For example, the subject of uketa (suffered) is unrealized in the following Japanese example (1):(1) sono-houkokusho-wa seifu i -ga The report pointed out that the government i agreed to a treaty and (it i ) suffered e... | 0 |
Human beings are not very good at asking questions about topics. They are often forgetful, which causes difficulties in expressing what is in their minds (Hasan, 2013) . Also sometimes, Humans, in front of a search engine, have difficulties to express their needs and intents as query terms. Imagine that you want to fin... | 0 |
A problem for translation is its context dependeuce. For every ambiguous word, the part of the context relevant for disambiguation must be identified (disambiguation strategy), and every word potentially occurring in this context nmst be assigned a bias for the translation decision (disambiguation ildorination).Manual ... | 0 |
This paper describes our approach for the First Multilingual Surface Realisation Shared Task (Mille et al., 2018 ). For the surface task the dependency parse trees were given unordered and the words lemmatized. The objective was to order the words in the sentences and to inflect the given lemmas. The data was provided ... | 0 |
With the rapid growth of the Internet, the web has become a powerful medium for disseminating information. People can easily share information of daily experiences and their opinion anytime and anywhere on the social media, such as blogs, Twitter and Facebook. Therefore, sentiment analysis studies have gained increasin... | 0 |
Statistical natural language processing is a challenging area in the field of computational natural language learning. Researchers of this field have an approach to language acquisition in which learning is visualized as developing a generative, stochastic model of language and putting this model into practice (Marcken... | 0 |
We investigate a compound information extraction (IE) problem from encyclopedia articles, which consists of two subtasks -recognizing structured information about entities and extracting the relationships between entities. The most common approach to this problem is a pipeline architecture: attempting to perform differ... | 0 |
Morphological processing and part-of-speech tagging are essential for many NLP tasks, including machine translation, information retrieval and parsing. In this paper, we describe a resource-light approach to the tagging of Russian. Because Russian is a highly inflected language with a high degree of morpheme homonymy (... | 0 |
The argumentative or discursive turn in policy analysis and political science more generally has long established the value of textual sources for the analysis of politics and policies (Fischer and Forester, 1993) . Traditionally, data sources such as interviews or newspaper reports were annotated using various methods... | 0 |
The use of computer software is an important part of the modern translation workflow (Zaretskaya et al., 2015; Schneider et al., 2019) . A number of tools are widely used by professional translators, most notably CAT tools and terminology management software. These tools increase translators' productivity, improve cons... | 0 |
Community question answering (CQA) systems such as Yahoo! Answers are online systems that allow signed-in users to ask, answer, and view questions and answers in a predetermined number of question categories. In Yahoo! Answers, there are two parts to a question: (I) the title -a brief description of the question, and (... | 0 |
Natural language understanding (NLU) requires analysis beyond the sentence-level. For example, an entity may be mentioned multiple times in a discourse, participating in various events, where each event may itself be referenced elsewhere in the text. Traditionally the task of coreference resolution has been defined as ... | 0 |
This paper presents improvements to a previously developed rule-based probabilistic system (Nawar and Ragheb, 2014) . We first make use of a unique Arabic feature, which is the word pattern to extract more rules for the system. Also, we have proposed a probabilistic Arabic grammar analyzer instead of a simple rule-base... | 0 |
Human language is not exact. For instance, an entity 1 may be referred by multiple names (i.e., polysemy), and also the same name may refer to different entities depending on the surrounding context (i.e., homonymy). The task of named entity disambiguation is to identify which names refer to the same entity in a textua... | 0 |
Statistical methods are widely used for machine translation. One of the popular statistical machine translation paradigms is the phrase-based model (PBSMT) (Marcu et al., 2002; Koehn et al., 2003; Och et al., 2004) . In PBSMT, errors in word reordering, especially in global reordering, are one of the most serious probl... | 0 |
The task of visual question answering (VQA) is to build a model for answering questions given an image-question pair. Recently, it has received great attention from computer vision community (Zhou et al., 2015; Kazemi and Elqursh, 2017; Tan and Bansal, 2019; Anderson et al., 2017; Kim et al., 2018; Singh et al., 2019) ... | 0 |
Bias and framing are central topics in the study of communications, media, and political discourse (Scheufele, 1999; Entman, 2007) , but they have received relatively little attention in computational linguistics. What are the linguistic indicators of bias? Are there lexical, syntactic, topical, or other clues that can... | 0 |
Keyphrase generation (KG) aims to generate of a set of keyphrases that expresses the high-level semantic meaning of a document. These keyphrases can be further categorized into present keyphrases that appear in the document and absent keyphrases that do not. Meng et al. (2017) proposed a sequence-to-sequence (Seq2Seq) ... | 0 |
Answer sentence selection (AS) is an important subtask of open-domain Question Answering (QA). Its input are a question Q and a set of candidate answer passages A = {A 1 , A 2 , ..., A N }, which may, for example, be the output of a search engine. The objective consists in selecting A i , i ∈ {1, ..., N } that contain ... | 0 |
The objective of NER is to classify all tokens in a text document into predefined classes such as person, organization, location, miscellaneous. NER is a precursor to many language processing tasks. The creation of a subtask for NER in Message Understanding Conference (MUC) (Chinchor, 1997) reflects the importance of N... | 0 |
The goal of machine translation is the translation of a text given in some source language into a target language. We are given a source string f J 1 = f 1 ...f j ...f J , which is to be translated into a target string e I 1 = e 1 ...e i ...e I . Among all possible target strings, we will choose the string with the hig... | 0 |
Question generation aims to automatically generate valid and coherent questions based on given context, which is widely applied to enrich question answering (QA) datasets, facilitate text comprehension (Ko et al., 2020) , seek clarification in conversation (Rao and Daumé III, 2019) , etc. Recently, neural encoder-decod... | 0 |
Real-time or simultaneous speech translation (ST) aims at translating a continuous speech input from one language to another with the lowest latency 1 and highest quality possible. In recent years, automatic speech translation systems have been devel-oped at scale, and their quality has improved significantly (Sperber ... | 0 |
Christian Wolff (1679-1754)'s philosophical ideas on the socalled 'mathematical method' are deemed greatly influential upon 18th century thinking about science (Frängsmyr, 1975, 654-55) . An interesting research question is whether the influence of Wolff's ideas can be more precisely assessed by using a mixed (quantita... | 0 |
Danish is primarily spoken in the northern hemisphere: in Denmark, on the Faroe islands, and on Greenland. Having roots in Old Norse, Danish bears similarities to other Scandinavian languages, and shares features with English and German.Previous tools and language resources for Danish have suffered from license restric... | 0 |
Unlike western languages, Chinese is unique due to its logographic writing system. Chinese users cannot directly type in Chinese words using a QW-ERTY keyboard. Pinyin is the official system to transcribe Chinese characters into the Latin alphabet. Based on this transcription system, Pinyin input methods have been prop... | 0 |
There is no doubt that in the last couple of years corpus-based machine translation (CBMT) approaches have been in focus. Among them, the statistical MT (SMT) approach has been by far more dominant, but the example-based machine translation (EBMT) Workshop at the end of 2009 1 and the new open-source systems (e.g. Open... | 0 |
The coreference and bridging annotation in the Prague Dependency Treebank (PDT) is one of the largest existing manually annotated corpora for pronominal, zero and nominal coreference and bridging relations. Contrary to the majority of similarly aimed corpus projects (Poesio 2004 , Poesio -Artstein 2008 , Recasens 2009 ... | 0 |
This paper describes the approach of the SemaNtic Analyis Project (SNAP) to Task 4 of SemEval-2014: Aspect Based Sentiment Analysis (Pontiki et al., 2014) . SNAP is a team of undergraduate students at the Corpus Linguistics Group, FAU Erlangen-Nürnberg, who carried out this work as part of a seminar in computational li... | 0 |
Developing an ability to understand natural language is a long-standing goal in NLP and holds the promise of revolutionizing the way in which people interact with machines and retrieve information (e.g., for scientific endeavor). To evaluate this ability, Richardson et al. (2013) proposed the task of machine comprehens... | 0 |
Affective computing deals with the recognition, interpretation, processing, and simulation of human affects. It is a highly interdisciplinary field at the heart of a broad range of technological applications in health care, media & advertisement, automotive, and others.Although emotions are a fundamental feature of hum... | 0 |
A Part-of-Speech (POS) tagger is a software that classifies words into its word classes or lexical categories (Bird et al., 2009) . POS tags and taggers have proven its importance in Natural Language Processing (NLP) when used in advanced NLP researches such as grammar checkers (Go and Borra, 2016) , information extrac... | 0 |
Les appellations des oeuvres visuelles de l'Antiquité classique sont au coeur du projet MonumenTAL -Monuments antiques et Traitement Automatique de la Langue -qui vise leur repérage automatique et leur étude par les historiens d'art et les archéologues. Compte tenu du grand nombre d'oeuvres concerné et de la multiplici... | 0 |
Supervised machine learning approaches require large amounts of labeled data to train robust machine learning models. Human-annotated gold labels have become increasingly important to modern machine learning systems for tasks such as spam detection, (movie) genre classification, sequence labeling, etc. The creation of ... | 0 |
Although conversational User Interfaces (CUIs) have gained popularity with the introduction of commercial personal assistants, these CUIs are mostly retrieval-based question answering (QA) systems that are incapable of holding a multi-turn conversation or providing follow-up information on the same topic or task. In ad... | 0 |
This paper deals with the problem of how to disambiguate the readings of sentences, analyzed by a given unification-based grammar (UBG).Apparently, there are many different approaches for almost as many different unification-based grammar formalisms on the market that tackle this difficult problem. All approaches have ... | 0 |
As language models are more prolifically used in language processing applications, ensuring a higher degree of fairness in associations made by their learned representations and intervening in any biased decisions they make has become increasingly important. Recent work analyzes, quantifies, and mitigates language mode... | 0 |
Large-scale, open Natural Language Inference (NLI) datasets (Bowman et al., 2015; Williams et al., 2018) have catalyzed the recent development of NLI models that exhibit close to human-level performance. However, the use of these NLI models for other downstream Natural Language Processing (NLP) tasks has met with limit... | 0 |
The semantics of tense and aspect has been a long standing issue in the study of formal semantics since the early days of Montague Grammar and a number of different ideas have been put forth to deal with them throughout the years. Recent proposals include the works of the following authors: Dowty (2012); Prior and Hasl... | 0 |
As one of the ultimate goals of natural language processing, Machine Reading Comprehension (MRC) has been attracting much attention from both the academical and industrial institutions (Richardson et al., 2013; Hermann et al., 2015) . Recently, most of the outstanding studies have benefited from the rapid development o... | 0 |
It has been continuously mentioned thatt some kind of latnguage knowledge is essential in goodquality speech understanding. Until recently, however, most research has focused mainly oil word recognition atnd one of the excellent recognition systems built to date is Sphinx developed by Lee [7] . Although SI)hinx atttain... | 0 |
Lifelong learning can be defined as the ability to continually acquire new and retain previous knowledge. This ability characterizes humankind, but it is also reflected in several artificial intelligence systems (Parisi et al., 2019; Biesialska et al., 2020) . There are many challenges that have to be solved in order t... | 0 |
The advent of the Internet has resulted in a massive information explosion. We need to have an effective and efficient means of locating just the desired information. The field of information retrieval (IR) is the traditional discipline that addresses this problem.However, most of the prior work in IR deal more with do... | 0 |
In recent years, several on-line broad-coverage semantic lexicons became available, including LDOCE (Procter, 1978) , WordNet (Miller, 1990) and HECTOR . (Kilgarriff, 1998a) . These lexicons have been used as a domainindependent semantic resource as well as an evaluation criteria in various Natural Language Processing ... | 0 |
This paper outlines NPiool, a noun phrase detector.At the heart of this modular system is reductionistic word-oriented morphosyntactic analysis that expresses head-modifier dependencies. Previous work on this approach, largely based on Karlsson's original proposal [Karlsson, 1990] , is documented in [Karlsson et ai., f... | 0 |
Whereas negation in predicate logic is well-defined and syntactically simple, negation in natural language is much complex. Generally, learning the scope of negation involves two subtasks: negation signal finding and negation scope finding. The former decides whether the words in a sentence are negation signals (i.e., ... | 0 |
When children learn to read, they first focus on each word individually and gradually learn to anticipate frequent patterns (Blythe and Joseph, 2011) . More experienced readers are able to completely skip words that are predictable from the context and to focus on the more relevant words of a sentence (Schroeder et al.... | 0 |
The large amount of medical literature hinders professionals from analyzing all the relevant knowledge to particular medical questions. Search engines are increasingly used to access such information. However, such systems retrieve documents based on the appearance of the query terms in the text despite the fact that t... | 0 |
Event recognition and classification has been pointed out to be very important to improve complex natural language processing (NLP) applications such as automatic summarization (Daniel et al., 2003) and question answering (QA) (Pustejovsky, 2002) . Natural language (NL) texts often describe sequences of events in a tim... | 0 |
In this paper, we discuss work on the detection of question and answer pairs in email threads, i.e., coherent exchanges of email messages among several participants. Email is a written medium of asynchronous multi-party communication. This means that, as in face-to-face spoken dialog, the email thread as a whole is a c... | 0 |
As a central task in natural language processing, relation extraction has been investigated on news, web text and biomedical domains. It has been shown to be useful for detecting explicit facts, such as cause-effect (Hendrickx et al., 2009) , and predicting the effectiveness of a medicine on a cancer caused by mutation... | 0 |
The sheer amount of scientific publications makes intelligent processing of papers increasingly important. Automated keyphrase extraction techniques can mitigate the severe difficulties arising when navigating in massive document collections. Hence, extracting keyphrases from scientific literature has generated substan... | 0 |
In last few years, large pretrained language models have gained a lot of popularity. These models were able to achieve state-of-the-art performance on various natural language processing tasks. But due to the higher resource requirement such as time and computation power, researchers have shifted their focus on develop... | 0 |
Vector representation of words are widely used in NLP tasks. Two approaches to word embeddings are usually contrasted: implicit (word2vec-like) and explicit (SVD-like). Implicit models are usually faster and consume less memory than their explicit analogues.Typically, word embedding algorithms produce two matrices both... | 0 |
In recent years, neural network models have become increasingly popular in NLP. Initially, these models were primarily used to create n-gram neural network language models (NNLMs) for speech recognition and machine translation (Bengio et al., 2003; Schwenk, 2010) . They have since been extended to translation modeling,... | 0 |
Unsupervised dependency parsers do not achieve the same quality as supervised or semi-supervised parsers, but in some situations precision may be less important compared to the cost of producing manually annotated data. Moreover, unsupervised dependency parsing is attractive from a theoretical point of view as it does ... | 0 |
Much attention has been paid to the generation and structure of the so-called multiple nominative constructions (MNC). Some of the constructions I will discuss in this paper are given in (1).(1) a. Mary-ka son-i yepputa. (Whole-Part Pattern: WPP) Mary-NOM hands-NOM prettỳ Mary's hands are pretty.' b. Mary-ka emeni-ka y... | 0 |
In the last years, deep learning algorithms have achieved state-of-the-art results in most NLP tasks such as textual inference, machine translation, hate speech detection (Socher et al., 2012) . Despite their accuracy, deep learning algorithms have a major downside, i.e. they require large amounts of data to be trained... | 0 |
Text similarity ranking is an important task in multiple domains, such as information retrieval, recommendations, question answering, and more. Recent approaches based on Transformer language models such as BERT (Devlin et al., 2019) benefit from effective text representations, but are limited in their maximum input te... | 0 |
Complex Question Answering, in which the question corresponds to multiple triples in knowledge base, has attracted researchers' attentions recently (Bao et al., 2014; Xu et al., 2016; Berant and Liang, 2014; Bast and Haussmann, 2015; Yih et al., 2015) . However, most of existing solutions employ the predefined patterns... | 0 |
Le découpage en mots est la première opération effectuée dans un traitement automatique de la langue. Mais le terme mot est linguistiquement inapproprié car il correspond en informatique à une entité, appelée token, délimitée par des séparateurs graphiques (blancs, retour à la ligne…). Il n'est pas nécessaire de rappel... | 0 |
The importance of effective language models in machine translation (MT) and automatic speech recognition (ASR) is widely recognised. n-gram models, in particular ones using Kneser-Ney (KN) smoothing, have become the standard workhorse for these tasks. These models are not ideal for languages that have relatively free w... | 0 |
The goal of summarization is to capture the important information contained in large volumes of text, and present it in a brief, representative, and consistent summary. A well written summary can significantly reduce the amount of work needed to digest large amounts of text on a given topic. The creation of summaries i... | 0 |
Alan Turing was a brilliant British mathematician who played a great role in the development of the computer. The imitation game, nowadays known as the Turing test, was devised by Turing as a method for deciding whether or not a computer program is intelligent. The Turing test takes place between an interrogator and tw... | 0 |
Identifying, classifying and talking about objects or events in the surrounding environment are key capabilities for intelligent, goal-driven systems that interact with other agents and the external world (e.g. smart phones, robots, and other automated systems), as well as for image search/retrieval systems. To this en... | 0 |
Most of the best models for natural language understanding are restricted to processing only a few hundred words of text at a time, preventing them from solving tasks that require a holistic understanding of an entire passage. Moving past this limitation would open up new applications in areas like news comprehension, ... | 0 |
Utterance and document level emotion recognition has received significant attention from the research community (Mohammad et al., 2018; Poria et al., 2020a) . Given the utterance Sudan protests: Outrage as troops open fire on protestors an emotion recognition system will be able to detect that anger is the main express... | 0 |
Large parse-annotated corpora have led to an explosion of interest in statistical parsing methods, including the development of highly successful models for parsing English using the Wall Street Journal Penn Treebank (PTB, (Marcus et al., 1994) ). Over the last 10 years, parsing performance on the PTB has hit a perform... | 0 |
Research and development for information extraction from biomedical literature (biotextmining) has been rapidly advancing due to demands caused by information overload in the genome-related field. Natural language processing (NLP) techniques have been regarded as useful for this purpose. Now that focus of information e... | 0 |
Le registre de langue dans lequel se situe un texte (à l'oral comme à l'écrit) apparaît comme un trait saillant. Il renvoie au contexte d'énonciation dans lequel il est -ou a été -produit (et qui comprend notamment la relation du locuteur avec ses interlocuteurs). Parmi les manifestations possibles de ce phénomène soci... | 0 |
Open-Domain Question Answering (ODQA) requires a system to answer questions using a large collection of documents as the information source. In contrast to context-based machine comprehension, where models are to extract answers from single paragraphs or documents, it poses a fundamental technical challenge in machine ... | 0 |
One-on-one instruction, i.e. tutoring, is one of the most effective forms of instruction. Intelligent Tutoring Systems (ITS) (Rus et al., 2013) have the potential to make effective and affordable "instruction-for-all" a reality since they do not suffer from traditional constraints such as lack of trained and expensive ... | 0 |
Machine Transliteration is the process by which a word written in source language is transformed into a target language, accurately and unambiguously, by preserving the phonetic aspects and pronunciation. Generally named entities or proper nouns are transliterated from one orthographic system to another. Based on the p... | 0 |
Due to processes of word formation such as derivation and compounding, lexical roots can be realized in different parts of speech and in different syntactic environments. For example, the derivational suffix -able can turn the verbal root derive in English into the adjective derivable, and the derivational suffix -ity ... | 0 |
The task of textual question answering (QA), in which a machine reads a document and answers a question, is an important and challenging problem in natural language processing. Recent progress in performance of QA models has been largely due to the variety of available QA datasets (Richardson et al., 2013; Hermann et a... | 0 |
In many natural language processing (NLP) applications, the performance of supervised machine learning models depends on the quality of the corpus used to train the model. Traditionally, labels are collected from multiple annotators/experts who are assumed to provide reliable labels. However, in reality, these experts ... | 0 |
Dependency grammar is a long-standing tradition that determines syntacto-semantic structures on the basis of word-to-word connections. It names a family of approaches to linguistic analysis that all share a commitment to typed relations between ordered pairs of words. Partially due to the powerful expressiveness of bi-... | 0 |
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