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Code-mixing and code-switching in multilingual societies are two of the most well-studied phenomena within the field of sociolinguistics (Gumperz, 1964; Auer, 1995; Myers-Scotton, 1997; Muysken, 2000; Cardenas-Claros and Isharyanti, 2009) . Generally, code-mixing is considered intra-sentential in the sense that it refe... | 0 |
In recent years, Transformer-based architectures have made enormous progress in neural question answering (QA) (Karpukhin et al., 2020 ) (Izacard and Grave, 2020). However, these models are still sensitive to query syntax and ambiguity (Buck et al., 2017) (Moon and Fan, 2020) . While data augmentation and lexical norma... | 0 |
Named Entity Recognition 1 (NER) can be treated as a tagging problem where each word in a sentence is assigned a label indicating whether it is part of a named entity and the entity type. Thus methods used for part of speech (POS) tagging and chunking can also be used for NER. The papers from the CoNLL-2002 shared task... | 0 |
Les techniques actuelles d'analyse sémantique de textes tendent de plus en plus à mettre en oeuvre une analyse locale fondée sur le repérage d'indices textuels de certaines informations sémantiques présentes dans les textes. La stratégie généralement adoptée par les systèmes d'extraction d'information (Pazienza, 1997) ... | 0 |
Romanian is a highly inflected language with a rich morphology. As dictionaries usually fail to cover the pronunciation aspects for all word forms in languages with such a rich and irregular morphology (Sef et al., 2002) , we believe that a data-driven approach is very suitable for syllabication and stress prediction f... | 0 |
With the development of network media, people can express their opinions on the Internet at any time, among which there will be some hope speech. Hope speech will encourage people to stand firm in their beliefs and follow the path of their goals. At the same time, comments or posts containing hope speech can often cont... | 0 |
The performance of an emotion classifier relies heavily on the quality of emotional speech data and the similarity of it to real world samples. As mentioned in [1] , there are three different categories of emotional speech: acted speech, elicited speech, and spontaneous speech. In this section we will describe the ways... | 0 |
A major thrust of research in sociolinguistics aims to uncover the relationship between social variables such as age and gender, and language use (Holmes and Meyerhoff, 2003; Eckert and McConnell-Ginet, 2013; Eckert, 1997; Wagner, 2012) . In line with scholars from a variety of disciplines, including the social science... | 0 |
Automatic speech recognition (ASR) technology has been made a dramatic progress and is currently brought to a pratical levels of performance assisted by large speech corpora and the introduction of deep learning techniques. However, this is not the case for low-resource languages which do not have large corpora like En... | 0 |
The current knowledge explosion in genetics and genomics poses a challenge to both researchers and medical practitioners. Traditionally, scientific reviews, which summarize and evaluate the literature, have been indispensable in addressing this challenge. OMIM (Online Mendelian Inheritance in Man) (OMIM 2000) , for exa... | 0 |
Several tools are available nowadays for alignment of pairs of languages. Among them, the bilingual word aligner GIZA++ (Och and Ney, 2003) can perform high quality alignments based on words statistics and is considered the most efficient tool. Three main criticisms may be addressed to this kind of tool.Firstly, as den... | 0 |
Information Extraction (IE) is to automatically pull out the structured information required by the users from a large volume of plain text. It normally includes three sequential tasks, i.e., entity extraction, relation extraction and event extraction. In this paper, we limit our focus on relation extraction.In early t... | 0 |
Automated Essay Scoring (AES) refers to the task of automatically grading student essays written in response to some prompt. Different approaches for AES have been proposed in literature, where it is modeled as a regression, ranking or a classification problem (cf. Yannakoudakis et al., 2011; Taghipour and Ng, 2016; Pi... | 0 |
Recently there has been an explosion in the number of people having informal, public conversations on social media websites such as Facebook and Twitter. This presents a unique opportunity to build collections of naturally occurring conversations that are orders of magnitude larger than those previously available. Thes... | 0 |
The probabilistic phrase-based models used in statistical machine translation (SMT) have been improved by integrating linguistic information during training stages. Recent attempts include, for example, the reordering of the source language syntax in order to align it closer to the target language word order (Collins e... | 0 |
Structural characteristics of signal representations are an important aspect in all pattern discovery and speech recognition tasks. There are numerous different methods for describing speech signals that use different types of signal transformations, including, e.g., FFT, cepstra and LP-coefficients. These approaches d... | 0 |
It is generally accepted that the event type of a sentence and in particular its aspectual value result from a complex interplay between lexical features of the predicate on one hand and its linguistic context on the other. In previous work by Siegel and McKeown (2000) , Zarcone and Lenci (2008) and Friedrich and Palme... | 0 |
Si les moteurs de recherche actuels sont suffisants pour répondre aux requêtes les plus courantes sur Internet, il n'existe pas actuellement d'outils permettant la formulation de requêtes s'appuyant sur des techniques de recherche avancées (filtrage sur le sens, élimination d'ambiguïtés, exclusion des sites marchands, ... | 0 |
Sememes are defined as minimum semantic units of word meanings, and there exists a limited close set of sememes to compose the semantic meanings of an open set of concepts (i.e. word sense). However, sememes are not explicit for each word. Hence, people manually annotate word sememes and build linguistic common-sense k... | 0 |
La production de ressources langagières est notoirement coûteuse 1 et représente de ce fait un goulot d'étranglement (language resources bottleneck), qui limite le développement d'outils de traitement automatique des langues (TAL). Ce phénomène est d'autant plus prégnant pour des langues dont l'intérêt économique ou po... | 0 |
With recent breakthroughs in pre-training, NLP models are showing increasingly promising performance on real-world tasks, leading to their deployment at scale for translation, sentiment analysis, and question answering. These models are sometimes used as black boxes, especially if they are only available as a service t... | 0 |
In the research fields of Chinese natural language processing (NLP), a high-performance Chinese word segmentor (CWS) is a useful preprocessing stage to produce an intermediate result for later processes, such as search engines, text mining and speech recognition, etc. The bottleneck of developing a high-performance CWS... | 0 |
For many low-resource and endangered languages, speech data is easier to obtain than textual data. The traditional method for documenting a language involves a trained linguist collecting speech and then transcribing it, often at a phonetic level, as most of these languages do not have a writing system. This, however, ... | 0 |
Information extraction has become a major task in text-mining. A large number of studies have been carried out with the objective of developing techniques to overcome the highly ambiguous and variable nature of natural language for the extraction of information from scientific text (Song et al., 2006) . Natural languag... | 0 |
With the growing demand for human-computer/robot interaction systems, detecting the emotional state of the user can substantially benefit a conversational agent to respond at an appropriate emotional level. Emotion recognition in conversations has proven valuable for potential applications such as response recommendati... | 0 |
While traditional Information Extraction (IE) (ARPA, 1991; ARPA, 1998) focused on identifying and extracting specific relations of interest, there has been great interest in scaling IE to a broader set of relations and to far larger corpora (Banko et al., 2007; Hoffmann et al., 2010; Mintz et al., 2009; Carlson et al.,... | 0 |
Considering the internal word structure when learning monolingual word embeddings has shown to produce better quality word representations, particularly for morphologically rich languages (Luong et al., 2013; Bojanowski and others, 2017) . However, the most popular approaches for learning cross-lingual embeddings have ... | 0 |
Models that can read text and reason about it in a particular context (such as an image, a paragraph, or a table) have been recently gaining increased attention, leading to the creation of multiple datasets that require reasoning in both the visual and textual domain (Johnson et al., 2016; Suhr et al., 2017; Talmor and... | 0 |
Automatic recognition of gene and protein names is a challenging first step towards text mining the biomedical literature. Advances in the area of gene and protein named entity recognition (NER) have been accelerated by freely available tagged corpora (Kim et al., 2003 , Cohen et al., 2005 , Smith et al., 2005 . Such c... | 0 |
Building infrastructures for human language technology is a non-trivial task. There can be numerous issues that have to be addressed, whether linguistic or non-linguistic. Unless carefully managed, the overall complexity can easily get out of control and seriously threaten the sustainability of the system. This may app... | 0 |
Scaling wide-coverage, constraint-based grammars such as Lexical-Functional Grammars (LFG) (Kaplan and Bresnan, 1982; Bresnan, 2001) or Head-Driven Phrase Structure Grammars (HPSG) (Pollard and Sag, 1994 ) from fragments to naturally occurring unrestricted text is knowledgeintensive, time-consuming and (often prohibiti... | 0 |
This paper describes a new extension to our system combination module in Dublin City University for the participation in the system combination task in the ML4HMT-2012 workshop. We incorporate alignment meta information to the alignment module when building a confusion network.Given multiple translation outputs, a syst... | 0 |
Machine learning strives to achieve universal application in solving arbitrary tasks rather than special functionalities and well-defined functions. This trend is reflected by the increasing importance of text understanding within the field of natural language processing (NLP). Extracting the context of a narrative pas... | 0 |
Most words in natural language exhibit polysemy, that is, they have multiple possible meanings. Each of these meanings is referred to as a sense, and word sense disambiguation is the process of identifying the intended sense of a target word based on the context in which it is used. The context of the target word consi... | 0 |
Recent years have seen increasing interest in textto-text generation tasks such as paraphrasing and text simplification, due in large part to their direct utility in high-level natural language tasks such as abstractive summarization. The task of sentence compression in particular has benefited from the availability of... | 0 |
Statistical Machine Translation systems are generally built on large amounts of parallel data. Typically, the training sentences are first aligned at the word level, then all phrase pairs that are consistent with the word alignment are extracted, scored and stored in the phrase table. While such extraction criterion pe... | 0 |
Avec l'augmentation du nombre de consultations médicales, la quantité de documents textuels concernant les patients a considérablement augmenté. Les divers compte-rendus de consultation ou de prise en charge hospitalière forment une masse de données importante et riche en informations sur le patient. Ces informations s... | 0 |
Coherence is a property of a well-written text that makes it different from a random set of sentences: sentences in a coherent text are connected in systematic ways such that each sentence follows naturally from previous ones and leads into the following ones (Halliday and Hasan, 1976; Grosz and Sidner, 1986) . Coheren... | 0 |
Recently, many advanced deep learning language models have been trained and proven to improve many natural language processing (NLP) tasks, such as text generation, summarization, machine translation, question answering and etc. General pretrained language models such as BERT (Devlin et al., 2018) and GPT-2 (Radford et... | 0 |
Recent intelligent open-domain chatbots (Adiwardana et al., 2020; Bao et al., 2020; Smith et al., 2020) have made substantial progress thanks to the rapid development of the large-scale pre-training approaches (Devlin et al., 2019; Radford et al., 2019; Brown et al., 2020) and the large amount of conversational data (D... | 0 |
In many situations such as disease outbreaks and natural calamities, we often need to develop an Information Extraction (IE) component (e.g., a name tagger) within a very limited time to extract information from low-resource languages (LLs) (e.g., locations where Ebola outbreaks from Hausa documents). The main challeng... | 0 |
A text, as the input of text processing applications, is composed of a string of characters and is interpreted based on the way it is segmented. Words and sentences are two segments in a text which carry meaning at different levels. Although the boundaries of words and sentences are specified to some extent in some scr... | 0 |
Neural network dependency parsers achieve state of the art performance Weiss et al., 2015; Andor et al., 2016) , but training them involves gradient descent on non-convex objectives, which is unstable with respect to initial parameter values. For some tasks, an ensemble of neural networks from different random initiali... | 0 |
Natural language processing methods producing shallow semantic output are starting to emerge as the next step towards successful developments in natural language understanding. Incremental, robust parsing systems will be the core enabling technology for interactive, speech-based question answering and dialogue systems.... | 0 |
Commonsense Question Answering (CQA) is a task that requires machines to not only understand the question, but also infer through external knowledge. For example, to answer the question in Figure 1 ("What do people typically do while playing guitar?"), it is necessary to discover the connection between the evidence "pl... | 0 |
Names play a significant role in many Natural Language Processing (NLP) and Information Retrieval (IR) systems. They have a critical role in Cross Language Information Retrieval (CLIR) and Machine Translation (MT) systems as the systems' performances are shown to positively correlate with the correct conversion of name... | 0 |
The nature of the training process for a speechrecognition system changes radically once the size of the vocabulary becomes larger than the number of words for which a user is willing to provide training tokens. Below this threshold, it is reasonable to make an independent model for each word in the vocabulary. Such a ... | 0 |
Much attention has recently been paid to non-task-oriented dialogue systems -or chatoriented dialogue systems-both in research (Higashinaka et al., 2014; Yu et al., 2016) and in industry. In addition to pure chat-oriented systems, some task-oriented dialogue systems can engage in chat-oriented dialogues (Lee et al., 20... | 0 |
Frequently recurring sequences of events in prototypical scenarios, such as visiting a restaurant and driving to work, are a useful source of world knowledge. Two examples are shown in Figure 1 , which are different variations of the "restaurant visiting" scenario, where events are partially ordered and can be flexible... | 0 |
The Verb Argument Browser (VAB) is a corpus query tool which is suitable for investigating the argument structure of verbs (Sass, 2008) . The paper cited defines the term argument as a phrase that appears in a syntactic relationship with the verb in a clause; and so we will use this term -as a synonym for dependent -fo... | 0 |
This paper describes the TraSpaS submission to the third shared task of the Balto-Slavic Natural Language Processing (BSNLP) Workshop at EACL 2021. The task focuses on recognizing named entities (NER), their normalization and linking across six Slavic languages. The participants are provided training data comprised of ... | 0 |
Various smart devices (e.g. smartphone, smart-TV, in-car navigating system) are incorporating spoken language interfaces, a.k.a. spoken dialogue systems (SDS), in order to help users finish tasks more efficiently. The key role in a successful SDS is a spoken language understanding (SLU) component; in order to capture t... | 0 |
For decades, the standard measures of performance for named entity recognition (NER) systems have been precision, recall, and F1 computed over entity mentions. 1 NER systems are primarily evaluated using exact match 2 F1 score, micro-averaged across mentions of all entity types. While perentity-type scores available fr... | 0 |
Joint segmentation and POS-tagging can improve upon a pipelined baseline by reducing error propagation and accommodating features that represent combined word and POS information. Three general approaches have been taken to perform joint inference, namely two-stage ensemble methods (Jiang et al., 2008a; Sun, 2011) , re... | 0 |
Document-level context-aware neural machine translation (NMT) aims to translate sentences in a document under the guidance of document-level context. Recent years have witnessed great improvement in context-aware NMT with extensive attempts at effectively leveraging document-level context ( (Tiedemann and Scherrer, 201... | 0 |
This paper describes Talk'n'Travel, a spoken language dialogue system for making complex air travel plans over the telephone. Talk'n'Travel is a research prototype system sponsored under the DARPA Communicator program (MITRE, 1999) . Some other systems in the program are Ward and Pellom (1999) , Seneff and Polifroni (2... | 0 |
Syntactic analysis is a central problem in language understanding that has received a tremendous amount of attention. Lately, dependency parsing has emerged as a popular approach to this problem due to the availability of dependency treebanks in many languages (Buchholz and Marsi, 2006; Nivre et al., 2007; McDonald et ... | 0 |
Recent work has shown evidence of substantial bias in machine learning systems, which is typically a result of bias in the training data. This includes both supervised (Blodgett and O'Connor, 2017; Tatman, 2017; Kiritchenko and Mohammad, 2018; De-Arteaga et al., 2019) and unsupervised natural language processing system... | 0 |
In a syntactic-transfer-based machine translation system, the transfer stage plays an important role and strongly affects on the translation result. Structural tree transfer is converting the syntactic trees of the source language (which is English in this experiment) into the ones of the target language (here is Vietn... | 0 |
Although discourse unit segmentation and connective detection are crucial for higher level shallow and deep discourse parsing tasks, recent years have seen more progress in work on the latter tasks than on predicting underlying segments, such as Elementary Discourse Units (EDUs). As the most recent overview on parsing ... | 0 |
In recent years, sentiment analysis, which mines opinions from information sources such as news, blogs, and product reviews, has drawn much attention in the NLP field (Hatzivassiloglou and McKeown, 1997; Pang et al., 2002; Turney, 2002; Hu and Liu, 2004; Pang and Lee, 2008) . It has many applications such as social med... | 0 |
In the past, historical documents and manuscripts were studied exclusively by a manual, paper-based approach. This limited the access to such documents to scholars who, on the one hand, know the historical variety of the language and, on the other hand, had access to the manuscripts. However, recent achievements in cor... | 0 |
In order to retrieve relevant answers, one of the basic steps in Question Answering (QA) systems is understanding the intent of questions (Chen et al., 2012; Cai et al., 2017) . This is particularly important for medical QA systems (Wu et al., 2020) , as consumer health questions -questions asked by patients -may use a... | 0 |
This paper addresses the issue of handling different variants of a given language by a deep language processing grammar for that language.In the benefit of generalization and grammar writing economy, it is desirable that a grammar can handle language variants -that share most grammatical structures and lexicon -in orde... | 0 |
The number of research papers has increased exponentially in recent years. In order to efficiently access this scientific resource, we need automated solutions for extracting information from these records. Citations in research papers are important for multiple reasons e.g. comparing novelty (Mishra and Torvik, 2016) ... | 0 |
With the advancements in Artificial Intelligence (AI), the gap between Natural Language Processing (NLP) and Computer Vision (CV) has been bridged by extensive research in multi-modal information analysis. The ability to use different modalities such as text, audio and video for different tasks, such as emotion classif... | 0 |
An information retrieval system returns documents presumed to be of interest to the user in response to a query. While there are a variety of different ways the retrieval can be accomplished, most systems treat the query as a pattern to be matched by documents. Unfortunately, the effectiveness of these word-matching sy... | 0 |
Speech repairs, as in example (1), are one kind of disfluent element that complicates any sort of syntax-sensitive processing of conversational speech.(1) and [ the first kind of invasion of ] the first type of privacy seemed invaded to meThe problem is that the bracketed reparandum region (following the terminology of... | 0 |
While humans experience emotions every day, the degree of one's emotions varies from one experience to another. To date, a vast majority of NLP and computational linguistics research deals with ground truth data constructed through the assignment of discrete labels to text messages by annotators. Conventionally, sentim... | 0 |
Answer selection (AS) is a crucial subtask of the open domain question answering (QA) problem. Given a question, the goal is to choose the answer from a set of pre-selected sentences (Heilman and Smith, 2010; Yao et al., 2013) . Traditional AS models are based on lexical features such as parsing tree edit distance. Neu... | 0 |
There are three basic stages of memory (e.g. Paller and Wagner, 2002) . All memories start with experience, which is reflected by text corpora (e.g. Hofmann et al., 2018) . The training of a language model then reflects the process of memory consolidation. The final stage is memory retrieval, which can be examined in p... | 0 |
Knowledge Graph Embeddings (KGE) are the stateof-art models for relational learning on large scale Knowledge Graphs (KG). They drive enterprise products ranging from search engines to social networks to e-commerce (Noy et al., 2019) . However, the analysis of their security vulnerabilities has received little attention... | 0 |
It was spring 2020 and it felt like we were in crisis mode. We wanted to teach a text and data mining (TDM) pilot course but because of social distancing measures we could not do it in a physical classroom. We had to learn new ways of interacting online and using a multitude of different technologies and we needed to d... | 0 |
Recently computer-driven conversational characters or virtual humans have started finding real-life applications ranging from education to health services and museums (Traum et al., 2005; Swartout et al., 2006; Kenny et al., 2009; Jan et al., 2009; Swartout et al., 2010) . As proliferation of these systems increases, t... | 0 |
Text segmentation is the task of splitting text into segments by placing boundaries within it. Segmentation is performed for a variety of purposes and is often a pre-processing step in a larger task. E.g., text can be topically segmented to aid video and audio retrieval (Franz et al., 2007) , question answering (Oh et ... | 0 |
The need to bridge the semantic gap between the semistructured "web of documents" and the structured "web of knowledge" (Buitelaar and Cimiano, 2008) has led to the development of various semantic enrichment systems in recent years. Named entity (NE) recognition and linking present a key component of semantic enrichmen... | 0 |
This paper illustrates an efficient way to quality check high level rule-based NLP applications for low resource languages with complex morphology like North Sámi. In particular, we develop a powerful regression testing tool for the rule-based open source North Sámi grammar checker Gram-Divvun (Wiechetek et al., 2019a)... | 0 |
Knowledge Bases (KBs) are widely used for representing information in a structured format. Such KBs, including Wikidata (Vrandečić and Krötzsch, 2014) , Google Knowledge Vault (Dong et al., 2014) , and YAGO (Suchanek et al., 2007) , often store information as facts in the form of triples, consisting of two entities and... | 0 |
The treatment of unbounded stress (Baek, 2018) , Uyghur backness harmony (Mayer and Major, 2018) , and Sanskrit n-retroflexion (Graf and Mayer, 2018) in subregular phonology has given rise to a rich collection of extensions of the tierbased strictly local languages (TSL; Heinz et al., 2011) as formal descriptions of th... | 0 |
Un corpus comparable est un ensemble de textes qui partagent entre eux un certain nombre de caractéristiques. La première de ces caractéristiques est de rassembler des documents qui portent sur des sujets proches. Par exemple, dans le contexte multilingue, les corpus comparables vont réunir les documents qui une thémat... | 0 |
Our aim is to propose a generic formalism as simple as possible but powerful enough to write real grammars for natural language and to handle complex linguistic structures. The formalism we propose can strongly simulate most rule-based formalisms used in linguistics. 1 Language utterances are both strongly structured a... | 0 |
To our knowledge, there is no ongoing effort to create a framenet for Finnish. This experiment gives information on whether it is feasible to build a preliminary framenet for Finnish by transferring the frames with their lexical units from Swedish. The building of semantically annotated language resources from scratch ... | 0 |
Word collocation is one source of information that has been proposed as a useful tool to post-process word recognition results( [1, 4] ). It can be considered as a constraint on candidate selection so that the word candidate selection problem can be formalized as an instance of constraint satisfaction. Relaxation is a ... | 0 |
The goal of this paper is to compile a method for multi-word term extraction, taking into account both the linguistic properties of Bulgarian terms and their statistical rates. Term extraction exploits well-established techniques that seem difficult to improve significantly. As in many other areas of computational ling... | 0 |
Compositional and distributional semantic models seem to provide complementary solutions for solving the same problem, that of assigning a proper "meaning" to a text segment. Specifically, while compositional models deal with the recursive nature of the language, providing a way to address its inherent ability to creat... | 0 |
Multiword Expressions (MWEs) are sequences of words that exhibit some kind of idiosyncrasy. This idiosyncrasy can be semantic, statistical, or syntactic 1 . Ivory tower, speed limit, and at large are examples of semantically, statistically and syntactically idiosyncratic MWEs respectively. Note that an MWE can be idios... | 0 |
Long-range contextual understanding has proven critical in many natural language processing (NLP) tasks. For example, the relevant context for correctly answering an open-domain question can arch over thousands of words (Chen et al., 2017) . Encoding long sequences via deep neural networks, however, has remained an exp... | 0 |
Discourse parsing aims to analyze the inner structure of texts, which is fundamental to many natural language processing applications, such as question answering and summarization. The construction of discourse corpora has promoted the development of discourse parsing techniques. In English, the widely-used discourse c... | 0 |
There is a very severe speed vs. accuracy tradeoff in stochastic context-free parsing, which can be explained by the grammar factor in the running-time complexity of standard parsing algorithms such as the CYK algorithm (Kasami, 1965; Younger, 1967) . That algorithm has complexity O(n 3 |P |), where n is the length in ... | 0 |
Word ordering often determines the meaning of a sentence; therefore how to utilize the position information of a word sequence has been an important topic in NLP and widely investigated recently. A common approach for modeling word ordering is to use recurrent neural networks (RNN), such as long short-term memory (LSTM... | 0 |
The objective of STS-Es is to score a pair of sentences in Spanish on the scale of 0 (the two sentences are on different topics) to 4 (the two sentences are completely equivalent, as they mean the same thing) (Agirre et al., 2014) . The textual similarity finds its utility in various NLP applications such as informatio... | 0 |
The Pascal RTE site defines entailment between two texts T and H as holding "if, typically, a human reading T would infer that H is most likely true" assuming "common human understanding of language as well as common background knowledge." While a few RTE3 entailments can be recognized using simple syntactic matching, ... | 0 |
Identification of the corresponding segments in sequences of phones is a necessary step in many applications in both diachronic and synchronic phonology. Usually we are interested in aligning sequences that represent forms that are related in some way: a pair of cognates, or the underlying and the surface forms of a wo... | 0 |
News reports usually consist of various modalities of tremendous information, especially all kinds of textual information and visual information, which make web users dazzled and lost. The situation gets worse on complex news events. To help readers quickly grasp the general information of the news, a more concise and ... | 0 |
Syntactic dependency parsing is attracting more and more research focus in recent years, partially due to its theory-neutral representation, but also thanks to its wide deployment in various NLP tasks (machine translation, textual entailment recognition, question answering, information extraction, etc.). In combination... | 0 |
Creating lexical entries is an important and time consuming task for any language. For lesser resourced languages with a rich morphology the task is particularly relevant. Building a lexicon requires often not only plenty of time and labour but also specific training. Thus, there is an obvious need for automating this ... | 0 |
The dependency graph (DG) is a packed shared data structure which consists of the nodes corresponding to the words in a sentence and the arcs showing dependency relations between the nodes. The scored DG has preference scores attached to the arcs and is widely used as a basis of the optimum tree search method. For exam... | 0 |
The main purpose of communication is to exchange intbrmation. On the part of a speaker, he may employ various strategies to organize the information he intends to couvey, in that some bear old information while others carry new information.Therefore, a discourse understanding model should be able to process the flow of... | 0 |
Professional translators use a number of tools to increase the consistency, quality and speed of their work. Some of these tools include spell checkers, text processing software, terminological databases and others. Among all tools used by professional translators the most important of them nowadays are translation mem... | 0 |
Legal information is often represented in textual form (e.g., legal cases, contracts, bills). Hence, legal text processing is a growing area in NLP with various applications such as legal topic classification (Nallapati and Manning, 2008; Chalkidis et al., 2019) , court opinion generation (Ye et al., 2018) and analysis... | 0 |
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