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Language models are fundamental to many natural language processing applications. In the most common approach, language models estimate the probability of the next word based on one or more equivalence classes that the history of preceding words is a member of. The inherent productivity of natural language poses a prob... | 0 |
Named entity recognition (NER) is a central component in natural language processing tasks. Identifying named entities is a key part in systems e.g. for question answering or entity linking. Traditionally, NER systems are built using conditional random fields (CRFs). Recent systems are using neural network architecture... | 0 |
Natural language processing is increasingly tackling new tasks over microblogs and social media, such as stance detection, sarcasm detection, and variations of sentiment analysis. Building on techniques used for traditional NLP, it is natural to attempt such tasks with inputs based solely on the content of the document... | 0 |
Event nouns are a subtype of nouns that lexically encode eventive information . In recent years, there has been growing interest in these nouns. Previous research in Mandarin Chinese includes patterns that they usually appear (Chu 2000; Han 2010; Ma 1995) , their classifiers (Ma 1995; Wang & Zhu 2000; , internal and ex... | 0 |
Formal documents such as legal and technical documents often form sublanguages. Previous studies have highlighted that capturing the sentence structure specific to the sublanguage is extremely necessary for obtaining high-quality translations especially between distant languages (Buchmann et al., 1984; Luckhardt, 1991;... | 0 |
In the last five years Neural Machine Translation (NMT) has evolved from a new and promising paradigm in Machine Translation (MT) to an established state-of-the-art technology. A few studies pose that performance difference between Statistical Machine Translation (SMT) and NMT is not as a great as one could imagine (Ca... | 0 |
State-of-the-art statistical machine translation (SMT) systems are often described as a two-pass process. In the first pass, decoding algorithms are applied to generate either a translation N-best list or a translation forest. Then in the second pass, various re-ranking algorithms are adopted to compute the final trans... | 0 |
The Allen Institute AI2 Diagrams dataset (hereafter AI2D) 1 contains nearly 5 000 grade-school level science diagrams, which have been annotated for their elements and the semantic relations that hold between them (Kembhavi et al., 2016) . The AI2D dataset was initially developed with two emerging computer vision tasks... | 0 |
This paper describes a general method for measuring the degree of cooperation of dialogue participants' behaviour. Central to the method is the idea, following Traum (1994) and Matheson et al. (2000) , that in dialogue obligations are continually created and resolved. Our contribution is a proposal for measuring non-co... | 0 |
Representing documents as fixed-length feature vectors is important for many document processing algorithms. Traditionally documents are represented as a bag-of-words (BOW) vectors. However, this simple representation suffers from being high-dimensional and highly sparse, and loses semantic relatedness across the vecto... | 0 |
Bracketing transduction grammar (BTG) (Wu, 1995) is an important subclass of synchronous context free grammar, which employs a special synchronous rewriting mechanism to parse parallel sentence of both languages.Due to the prominent advantages such as the simplicity of grammar and the good coverage of syntactic diversi... | 0 |
As training neural networks becomes an organizational and multi-million dollar venture (Brown et al., 2020) , it is imperative to quantifiably predict the benefits of scaling up neural networks. In this paradigm, machine learning is an engineering effort, in which money can buy resources (data, compute) and the main co... | 0 |
When students learn programming, they have the benefit of integrated development environments, which support them throughout the entire application development process: from writ-ing the code, through testing, to documentation. In addition, these environments offer support and automation of common tasks, e.g., user int... | 0 |
The automatic recognition of irony is, still nowadays, a challenging task to be performed both by human annotators and automatic NLP systems (Mihalcea and Pulman, 2007; Reyes et al., 2010; Kouloumpis et al., 2011; Maynard and Funk, 2011; Reyes et al., 2012; Hernández Farías et al., 2016; Sulis et al., 2016) . The growi... | 0 |
In recent years, neural networks have been widely used to grade student essays automatically and achieve state-of-the-art performance. In particular, a distributed representation is learned for an essay with variant neural networks and a linear layer is then used to produce the final score. Existing researches focus on... | 0 |
There is no doubt about the increasing need of owning accurate and broad coverage general lexical/semantic resources for developing NL applications. These resources include Lexicons, Lexical Databases, Lexical Knowledge Bases (LKBs), Ontologies, etc. Many researchers believe that for effective NLP it is necessary to bu... | 0 |
In the ideal world, a knowledge representation technique, which solves the gamut of reading comprehension tasks from question answering to university entrance examinations, shows the ubiquity and understanding in all the corpora. In fact, for machine reading comprehension, developing a ubiquitous and well-defined knowl... | 0 |
Text classification is one of the fundamental tasks in natural language processing (NLP) in which the objective is to categorize text documents into one of the predefined classes. This task has a lot of applications such as topic classification of news articles, sentiment analysis of reviews, email filtering, etc. Text... | 0 |
In the past two decades, many resources have been invested to develop state-of-the-art text processing tools for Dutch 1 . Similar to other reported languages, these tools, which have all been developed with standard text in mind, show a significant drop in performance when applied to usergenerated content (UGC). This ... | 0 |
This article describes the collaborative work on applying the newly proposed ISO standard for dialogue act annotation to the Switchboard Dialogue Act (SWBD-DA) Corpus, as part of our on-going effort to promote interoperability of standardized linguistic annotations with the ultimate goal of developing shared and open l... | 0 |
The ability to distinguish statistically different populations of speakers or writers can be an important asset in many NLP applications. In this paper, we describe a method of using document similarity measures to describe differences in behavior between native and non-native speakers of English in a prompt response t... | 0 |
In recent years, neural machine translation (NMT) has achieved great advancement (Nal and Phil, 2013; Sutskever et al., 2014; Bahdanau et al., 2015) . However, two difficulties are encountered in the practical applications of NMT. On the one hand, training a NMT model for a spe- * cific domain requires a large quantity... | 0 |
Information extraction has long been an active subarea of natural language processing (NLP) (Onyshkevych et al., 1993; Freitag, 2000) . A particularly important class of extraction tasks is ERE detection in which an object, typically an element in a knowledge base, is created for each ENTITY, RELATION, and EVENT identi... | 0 |
One of the major common challenges for machine translation (MT) is the different order of the same conceptual units in the source and target languages. In order to get a fluent and adequate translation in the target language, the default phrase-based statistical machine translation (PB-SMT) system implemented in MOSES ... | 0 |
Sentiment analysis systems have continuously improved the quality of polarity classifications of entire product reviews. For numerous real-world applications, however, classification on such a coarse level is not suitable. Even in their most enthusiastic reviews, users still tend to mention negative aspects of a partic... | 0 |
Considering Argument Mining (AM) for Social Good implies a strong conceptual shift: the discourse exchange is not to be interpreted as a competition to be won by the most persuasive contribution 1 , but rather as a cooperative endeavor in which each individual contribution represents a move towards a shared goal. If ar... | 0 |
While phonological research often focuses on categorical generalizations, a growing body of research addresses the representation and learning of variable processes and exceptional processes, where application is lexically conditioned (see Coetzee and Pater (2011) and Pater (2010) for overviews). A few recent studies h... | 0 |
In speech and language processing, smoothing is essential to reduce overfitting, and Kneser-Ney (KN) smoothing (Kneser and Ney, 1995; Chen and Goodman, 1999) has consistently proven to be among the best-performing and most widely used methods. However, KN smoothing assumes integer counts, whereas in many NLP tasks, tra... | 0 |
Relation Extraction (RE) from text as defined in ACE (Doddington et al., 2004) concerns the extraction of relationships between two entities. This is typically carried out by applying supervised learning, e.g. (Zelenko et al., 2002; Culotta and Sorensen, 2004; Bunescu and Mooney, 2005) by using a handlabeled corpus. Al... | 0 |
The advent of pre-trained language models (Devlin et al., 2019; Radford et al., 2019) has transformed natural language processing. The dominant paradigm has shifted away from designing task-specific architectures towards transfer learning. Fine-tuning pre-trained models on downstream datasets achieves strong performanc... | 0 |
Spelling is an essential literacy and life skill, the basics of which are taught to children during their first few years of school (Berkling, Kay, 2018) . Cultivating spelling is considered to be a good reflection of children's understanding and learning of the alphabet, as well as a good predictor of their reading sk... | 0 |
In natural language processing (NLP), text generation is an important research topic that aims to automatically produce understandable text in human language from input data (Li et al., 2022) . In recent decades, various approaches have been widely applied to a variety of text generation tasks Gehring et al., 2017; Li ... | 0 |
Automatic paraphrasing is a transformation of expressions into semantically equivalent expressions within one language. It is expected for various applications, such as information retrieval, machine translation and a reading/writing aid.Automatic paraphrasing of Japanese text has been studied by many researchers after... | 0 |
Recent development in Natural Language Processing (NLP) heavily benefits from a high level of maturity of open-source frameworks, such as Fairseq (Ott et al., 2019) or HuggingFace Transformers (Wolf et al., 2020) . Thanks to the standardized interfaces, these libraries allow for immediate experimentation with the most ... | 0 |
With more than 7000 languages in the world (Ethnologue, 2019) and the need to support multiple input and output languages, it is one of the most pressing challenge for the speech and language community to develop and deploy speech processing systems in yet unsupported languages rapidly and at reasonable costs (Schultz,... | 0 |
A Treebank can be defined as a syntactically processed corpus. It is a language resource containing annotations of information at various linguistic levels such as words, phrases, clauses and sentences to form a 'bank of linguistic trees'. There are many Treebanks built for different languages such as the Penn Treebank... | 0 |
Systems for the recognition of biomedical named entities have traditionally worked on a 'first-best' approach, where all of the entities recognised have equal status, and precision and recall are given roughly equal importance. This does not reflect that fact that precision is of greater importance for some application... | 0 |
The drastic increase in demands for the capability to assist trans-lingual conversations, triggered by IT technologies such as the Internet and the expansion of borderless communities such as the increased number of EU countries, has accelerated research activities on speech-to-speech translation technology. Many resea... | 0 |
Social media content has, for many people and organizations, changed the way we interact and share information. This content (ranging from blogs, fora, reviews, and various social networking sites) has specific characteristics that are often referred to as the five V's: volume, variety, velocity, veracity, and value. S... | 0 |
In Japan, the television reception environment has become quite diverse in recent years. In addition to analog broadcasts, BS (Broadcast Satellite) digital television and data broadcasts have been operating since 2000. At the same time, TV operations for receiving such broadcasts are becoming increasingly complex, and ... | 0 |
The analysis of nominal compound constructions has proven to be a recalcitrant problem for linguistic semantics (Bergsten 1911 , Jespersen 1942 , Marchand 1970 , Lees 1970 , Downing 1977 , Levi 1978 , Warren 1987 , and their analysis has presented a serious challenge for natural language processing systems (Finin 1980 ... | 0 |
During the last decade, SGML and XML have become an important interchange format for linguistic data, be they created manually by linguists, or automatically by natural language processing (NLP) components. LT-XML (Brew et al. 2000) , XCES (Ide and Romary 2001) and many other are examples for XML-based or XML-supportin... | 0 |
Online support groups are a rich source of information concerning patient experiences, but they are far different from clinical content. Instead of "The patient presents with…" and "denies vomiting," patients may speak of their "doc" and "rheumy." There may be utterances like "LOL" (laugh out loud) and "Hugs." Patients... | 0 |
Grammatical analysis tasks, e.g., part-of-speech tagging, are rather successful applications of natural language processing (NLP). They are comprehensive, i.e., they operate under the assumption that all grammatically-relevant parts of a sentence will be analyzed: We do not expect a POS tagger to only know a subset of ... | 0 |
Rap is a musical form originating from America in 1970s, and has quickly developed as one of the mainstream music genres in the world (Keyes, 2004) . With the rapid development of artificial intelligence, automatic rap lyrics generation has drawn attention from academia (Potash et al., 2015; Malmi et al., 2016; Liang e... | 0 |
Bundeli is spoken in regions of Madhya Pradesh and Uttar Pradesh, in a region known as Bundelk-hand, which encompasses several administrative districts in India. While the 2001 census identifies 3,070,000 Bundeli speakers, Ethnologue estimates 20,000,000 speakers 1 . Inspite of the large population, Bundeli, often cons... | 0 |
Combinatory categorial grammar (CCG) is a lexicalized grammatical formalism, where the lexical categories (also known as supertags) of the words in a sentence provide informative syntactic and semantic knowledge for text understanding. Therefore, CCG parse often provides useful information for many downstream natural l... | 0 |
The theory of dependency grammar culminated in the seminal book by Lucien Tesni ere, Tesni ere, 1959, to which also today's leading scholars pay homage, see, e.g., Mel' cuk, 1987 . Unfortunately, Tesni ere's book is only available in French, with a partial translation into German, and subsequent descriptions of his wor... | 0 |
Learning representations for words from their contexts provides us with new instruments to tackle natural language processing (NLP) tasks. In many supervised NLP tasks the training data is limited and expensive but plain text is easily accessible thanks to the web. In opposition to NLP systems that considers words as a... | 0 |
Speech synthesis systems are expected to play important roles in advanced user-friendly human-machine interfaces. Wishing to realize an as good as possible text-to-speech system for the Romanian language the research started with the •development of the software for monotonous speech synthesis, which simply concatenate... | 0 |
Multi-task Learning (MTL), which involves the simultaneous learning of multiple tasks, can achieve better performance than learning each task independently (Caruana, 1993; Ando and Zhang, 2005) . It has achieved great success in various applications, ranging from summary quality estimation (Kriz et al., 2020) to text c... | 0 |
Developing intelligent chatbots and dialog systems is of great significance to both commercial and academic camps. A good conversational agent enables enterprises to provide automatic customer services and thus reduce human labor costs. For academia, it is challenging yet appealing to build up such an intelligent chatb... | 0 |
Event Extraction is an important task in Information Extraction (IE) that aims to identify event triggers and arguments from unstructured texts and classify them into predefined categories. Compared to other IE tasks such as name tagging, the annotations for Event Extraction are more costly because they are structured ... | 0 |
Natural language processing (NLP) has advanced drastically in the last decade with the design of larger and more sophisticated models, availability of larger corpora and increasing computational power. Pretrained word embeddings (Mikolov et al., 2013; Pennington et al., 2014) popularized the use of distributed word rep... | 0 |
This paper describes the statistical machine transliteration system used for participation in the NEWS 2011 shared task workshop. We participated in English to Persian task and used three different systems for transliteration generation.There have been a few researches on Persian language (Karimi et al., 2007) . The qu... | 0 |
We adopt, evaluate, and improve upon the two-step NLU pipeline, described in , which aims to incrementally tame the variation of incoming natural language that the robot must interpret before responding. For each domain in which it operates, the robot must determine whether or not the commands it receives correspond to... | 0 |
Multimodal Machine Translation is the task of translating text using information in other modalities (such as images) as auxiliary cues. It has been recently framed as a shared task as part of the last two editions of the Conference on Machine Translation (WMT16, WMT17) (Specia et al., 2016; Elliott et al., 2017) . Wit... | 0 |
There is growing interest in methods that incorporate human domain knowledge in machine learning algorithms, either as priors on model parameters or as constraints in an objective function. Such approaches lend themselves well to natural language tasks, where input features are often discrete variables that carry seman... | 0 |
There are currently several key problems for the practical data-driven (rather than hand-crafted) development of task-oriented dialogue systems, 1 Dataset available at https://bit.ly/babi_plus among them: (1) large amounts of dialogue data are needed, i.e. thousands of examples in a domain; (2) this data is usually req... | 0 |
In pronoun-dropping (pro-drop) languages such as Arabic (Eid, 1983) , Chinese (Li and Thompson, 1979) , Italian (Di Eugenio, 1990 ) and other romance languages (e.g., Portuguese, Spanish), Japanese (Kameyama, 1985) , and others (Kim, 2000) , certain arguments can be omitted in which a pronoun is used in English: such a... | 0 |
Rich cross lingual resources including large translation dictionaries are necessary in order to realize working cross-lingual NLP applications. However, it is infeasible to build such resources for all language pairs, because there are many languages in the world. Actually, while rich resources are available for severa... | 0 |
For many NLP researchers from both academia and industry, sarcasm detection has been one of the most focused areas of research among many research problems like code-mixed sentiment analysis (Lal et al., 2019) , detection of offensive or hate speeches (Liu et al., 2019) , questionanswering(Soares and Parreiras, 2018), ... | 0 |
Semantic parsing is the task of mapping natural language (NL) utterances to meaning representations (aka programs) that can be executed against a real-world environment such as a knowledge base or a relational database. While neural sequence-to-sequence models (Dong and Lapata, 2016; Jia and Liang, 2016a) have achieved... | 0 |
The existence of various English exam products provides a useful and fair way for language learners to measure their English skills accurately. It also offers a well-accepted standard to help schools and companies to quantitatively judge whether their non-native English applicants meet the compulsory language requireme... | 0 |
Machine Reading Comprehension (MRC) has become a popular task in NLP, aiming to understand a given passage and answer the relevant questions. With the wide availability of MRC datasets (Rajpurkar et al., 2016; Cui et al., 2019) and deep learning models (Yu et al., 2018; Ding et al., 2019 ) (including pre-trained langua... | 0 |
Having large and high-quality parallel corpora is critical for neural machine translation (NMT). One way to create such a resource is to mine the web (Resnik and Smith, 2003) . Once texts are crawled from the web, they form large collections of data in different languages. To find parallel sentences, a natural way is t... | 0 |
Information Retrieval in full texts is one of the challenges of the next years. Web engines attempt to select among the millions of existing Web Sites, those corresponding to some input request. Newspaper archives is another exam-1212 ple: there are several gigabytes of news on electronic support, and the size is incre... | 0 |
The Revision Requirements task aims to recognize whether or not a sentence requires revision. Revision Requirements prediction not only acts as a standalone tool for grammar correction but also has potential applications in natural language processing (NLP) such as ambiguity detection, machine translation refinement, s... | 0 |
This paper proposes a smoothing model for probabilistic subcategorization (SCF) lexicons of lexicalized grammars acquired from corpora. Here, an SCF lexicon consists of pairs of words and lexical (SCF) types (e.g, tree family), from which individual lexical entry templates are derived by lexical rules (Jackendoff, 1975... | 0 |
Maximum entropy (Maxent) is widely used in many areas such as natural language processing (NLP) and document classification. Maxent models the conditional probability as:EQUATIONS w (x, y) ≡ e P t wtft(x,y) , T w (x) ≡ y S w (x, y), where x indicates a context, y is the label of the context, and w ∈ R n is the weight v... | 0 |
For humans, the task of determining semantic relationships may entail complicated inference based on concepts' contexts (Yee and Thompson-Schill, 2016; Zhang et al., 2020) and commonsense knowledge (e.g., causal relations; Chiang et al., 2021), and for labeling relations between entities in texts the task may depend on... | 0 |
Spell checking is a routine processing task for every written language, which is an automatic mechanism to detect and correct human spelling errors. Given sentences, the goal of the task is to return the locations of incorrect words and suggest the correct words. However, Chinese spell checking (CSC) is very different ... | 0 |
Many NLP tasks such as part-of-speech tagging, parsing and named entity recognition have become sufficiently accurate that they are no longer solely an object of research, but are also widely deployed in production systems. These systems can be run on billions of documents, making the efficiency of inference a signific... | 0 |
One of the characteristic features of women's speech, according to Lakoff (1975:53-54) , is that women use, among others, hedges such as well, y'know, kinda and intensive so more frequently than men. Quirk and Greenbaum (1973) calls them "adverbial qualification" as being points on an intensity scale which may be high ... | 0 |
Discourse relation labelling aims at predicting the most proper discourse relation between two discourse units such as clauses, sentences, and groups of sentences. The labelling task can be done at the intra-sentential and the inter-sentential levels depending on the analysis units. Several schemes have been proposed t... | 0 |
Chatbots, a type of dialogue system, have been widely deployed for commercial applications, such as flight booking and troubleshooting support. One key step of frame-based chatbots is to extract the intent of the user, i.e. to recognize the goal of the user's query (Jurafsky and Martin, 2019) . While the task of single... | 0 |
This paper presents a logical formalization of Tree Adjoining Grammar (TAG) (Joshi, Levy and Takahashi 1975) . TAG deals with lexicalized trees and two operations are available: substitution and adjunction. A set of (elementary) trees is associated to each lexical item. TAG is a tree-rewriting system: the derivation pr... | 0 |
The HCRC Map Task corpus has been collected and transcribed in Glasgow and Edinburgh, and recently published on CD-ROM (HCRC 1993) . This effort was made possible by funding from the British Economic and Social Research Council.The group which designed and collected the corpus covers a wide range of interests and the c... | 0 |
The development and maintenance of test suites is integral to the process of writing deep linguistic grammars (Oepen and Flickinger, 1998; Butt and King, 2003) . Such test suites typically contain handconstructed examples illustrating the grammatical phenomena treated by the grammar as well as representative examples t... | 0 |
After the development of Princeton WordNet (Fellbaum, 2012) , two main approaches were widely exploited to create WordNet for any given language: dictionary-based concept (Brazilian Portuguese WordNet, Dias-da-Silva et al., 2002) and translation-based approach (see for example, Turkish WordNet, Bilgin et al., 2004) . T... | 0 |
Bilingual lexicons map words in one language to their translations in another, and can be automatically induced by learning linear projections to align monolingual word embedding spaces (Artetxe et al., 2016; Smith et al., 2017; Lample et al., 2018, inter alia) . Although very successful in practice, the linear nature ... | 0 |
While automated scoring of open-ended written discourse has been approached by several groups recently (Rudner & Gagne, 2001; Shermis & Burstein, 2003) , automated scoring of spontaneous spoken language has proven to be more challenging and complex. Spoken language tests are still mostly scored by human raters. However... | 0 |
Current statistical machine translation systems suffer from major accuracy degradation in distant languages, primarily because they utilize exceptionally dissimilar word orders. One promising solution to this problem is preordering, in which source sentences are reordered to resemble the target language word orders, af... | 0 |
As a part of Requirements Engineering (RE), requirements analysis is "a critical task in software development as it involves investigating and learning about the problem domain in order to develop a better understanding of stakeholders actual goals, needs, and expectations" (Hull et al., 2017) . However, it is a challe... | 0 |
Performance on NLP tasks drops significantly when moving from training sets to held-out data (Petrov et al., 2010) . One cause of this drop is words that do not appear in the training data but appear in test data, whether in the same domain or in a new domain. We refer to such out-of-trainingvocabulary (OOTV) words as ... | 0 |
Representing words as vectors in some latent space has long been a central idea in natural language processing. The distributional hypothesis, perhaps best stated as "You shall know a word by the company it keeps" (Firth, 1957) , has had a long and productive history, as well as a recent revival in neural-network-based... | 0 |
Many situations call for a parser to return a kbest list of parses instead of a single best hypothesis. 1 Currently, there are two efficient approaches known in the literature. The k-best algorithm of Jiménez and Marzal (2000) and Huang and Chiang (2005) , referred to hereafter as LAZY, operates by first performing an ... | 0 |
Determining the attachments of prepositions and subordinate conjunctions is an important problem in parsing natural language. It is also an old problem that continues to elude a complete solution. A classic example of the problem is the sentence "I saw a man with a telescope" , where who had the telescope is ambiguous.... | 0 |
Machine translation (MT) systems are becoming more widely used by ordinary people as well as by expert translators, with numerous web sites offering free translation services. In view of this situation, an international research project called the ICE (Intercultural Collaboration Experiment) project was launched to inv... | 0 |
Bien que la majorité des systèmes de reconnaissance de la parole (SRAP) soient, à l'heure actuelle, basés sur des méthodes statistiques, ils peuvent différer sur plusieurs points (méthodes de paramétrisation du signal, modélisation acoustique et linguistique, algorithmes de décodage ...).La combinaison de SRAP a pour o... | 0 |
Thematic fit estimations can be quite useful for many NLP applications and also for cognitive models of human language processing difficulty, since human processing difficulty is highly sensitive to semantic plausibilities (Ehrlich and Rayner, 1981) . For example, we expect that after the word mash, banana would be eas... | 0 |
In various tasks and applications of natural language processing and of biomedical informatics (i.e., query expansions, information retrieval, text mining, information extraction or terminology matching), it is important to be able to decide whether two terms (i.e., acetone anabolism and acetone biosynthesis, replicati... | 0 |
Je n'ai pas besoin d'insister sur l'importance de la phraséologie pour la linguistique en général et pour le TALN en particulier. Cela serait essayer d'enfoncer une porte ouverte : sur ce point, la communauté linguistique est d'accord. Ce sur quoi on n'est pas tellement d'accord est le contenu exact de la notion « phra... | 0 |
Following the success of BERT (Devlin et al., 2018) (Bidirectional Encoder Representations from Transformers) in the general domain, the pretrain-andfinetune approach has been used in the Biomedical domain. With large scale free text available from PubMed and PubMed central (millions of articles), biomedical domain has... | 0 |
Bridging (Clark, 1975) plays an important role in establishing entity coherence in a text. In contrast to direct anaphors, which indicate the coreference relation between a nominal expression and its antecedent, bridging anaphors or associative anaphors link to their antecedents via non-identical relations. Bridging re... | 0 |
One of the first tasks confronting researchers developing a spoken language system is the collection of data for analysis, system training, and evaluation. Since people do not always say grammatically wellformed sentences during a spoken dialogue with a computer, the currently available read speech databases may not ca... | 0 |
A language model (LM) is a central module for natural language generation (NLG) tasks (Young et al., 2018) such as machine translation , dialogue response generation (Li et al., 2017) , image captioning (Lin et al.) , and related tasks. Given a trained LM, finding the best way to generate a sample from it has been an i... | 0 |
"I sit in my chair all day and work and workMeasuring words against each other."-Conrad Aiken Improvisations: Light And SnowWhile metaphors are part of everyday language, in poetry they are vital. Metaphorical language, in contrast with literal or non-metaphorical language, "mak[es] use of structure imported from a com... | 0 |
Providing computer the ability to understand the abstract meaning of real world is a fundamental tasks. Given a pair of news articles, this task seek to evaluate the semantic similarity between them, which focuses on the real world-happenings covered in the news articles. It's a regression problem for measuring similar... | 0 |
Named entity recognition (NER) is a popular sequence labeling task in the natural language processing (NLP) arena. It has numerous applications in several computational linguistic tasks including designing efficient search systems, data mining, and document indexing. However, prior studies mostly focused on identifying... | 0 |
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