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This paper presents LexMeta, a metadata model for the description of lexical resources, such as dictionaries, word lists, glossaries, etc., to be used in language data catalogues mainly targeting the lexicographic and broader humanities communities but also users exploiting such resources in their research and applications. A comparative review of similar models is made in order to show the differences and commonalities with LexMeta. To enhance semantic interoperability and support the exchange of (meta)data across disciplinary and general catalogues, the most influential models for our purposes, namely FRBR (used in library catalogues) and META-SHARE (used for language resources), are selected as a base for the design of LexMeta. We discuss how these models are aligned and extended with new properties as required for the description of lexical resources. The formal representation of the model following the Linked Data paradigm aims to further enhance the semantic interoperability. The choice to implement it in two formats (as an RDF/OWL and as a Wikibase ontology) facilitates its adoption and hence its enrichment, yet poses challenges as to their synchronisation, which are addressed through automatic workflows. We conclude with ongoing and planned activities for the improvement of the model.

Research in the area of ​​the interconnection of lexical resources represents a real challenge, because it addresses the difficult problem of semantic understanding and, more precisely, the disambiguation of the meaning of the words - Word Sense Disambiguation (WSD). In the current and prospective context of the information society, the existence of the digital format of the fundamental works of a national culture is strictly necessary. It is a topical issue throughout the world of creating a representative corpus of a language accessible through the Internet, the corpus being a concrete, clear picture of the use of that language. In this study we will describe the development of a Romanian language GOLD corpus, related to the multiple meanings existing for various words. We propose a corpus annotation standard, based on three lexical resources as follows: the Thesaurus Dictionary of the Romanian Language in electronic format (eDTLR), from which we extracted a list of words with multiple meanings; from the Reference Corpus for Contemporary Romanian Language (CoRoLa) we extracted contexts in which these words were founded and from the the Romanian WordNet (RoWN) resource, we took into account the sense meaning of the word from the corpus context. [ABSTRACT FROM AUTHOR]

In this paper we will present an approach for interconnecting some of the most important lexical resources for the Romanian language, among which the Corpus for Contemporary Romanian Language (CoRoLa), Romanian WordNet, the Thesaurus Dictionary of Romanian Language in Electronic Format (eDTLR). We will show how they are indexed to each other in order to obtain a standard interconnected structure, and then, we will present a general architecture of a system dedicated to interconnecting lexical resources "on the fly". [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive survey of corpora and lexical resources available for Turkish. We review a broad range of resources, focusing on the ones that are publicly available. In addition to providing information about the available linguistic resources, we present a set of recommendations, and identify gaps in the data available for conducting research and building applications in Turkish Linguistics and Natural Language Processing. [ABSTRACT FROM AUTHOR]

This paper presents LexMeta, a metadata model for the description of lexical resources, such as dictionaries, word lists, glossaries, etc., to be used in language data catalogues mainly targeting the lexicographic and broader humanities communities but also users exploiting such resources in their research and applications. A comparative review of similar models is made in order to show the differences and commonalities with LexMeta. To enhance semantic interoperability and support the exchange of (meta)data across disciplinary and general catalogues, the most influential models for our purposes, namely FRBR (used in library catalogues) and META-SHARE (used for language resources), are selected as a base for the design of LexMeta. We discuss how these models are aligned and extended with new properties as required for the description of lexical resources. The formal representationof the model following the Linked Data paradigm aims to further enhance the semantic interoperability. The choice to implement it in two formats (as an RDF/OWL and as a Wikibase ontology) facilitates its adoption and hence its enrichment, yet poses challenges as to their synchronisation, which are addressed through automatic workflows. We conclude with ongoing and planned activities for the improvement of the model. [ABSTRACT FROM AUTHOR]

This article aims to provide an overview of current trends in vocabulary teaching, and to highlight several initiatives taken by the authors for teaching and/or improving French vocabulary for native learners (L1), and foreigners (French as second or foreign language, L2). After a cross disciplinary theoretical overview on the notions of ‘lexicon’ and ‘context’ we describe different activities having in common the necessity of considering the context in its broadest sense, that is, from a lexical, textual, discursive, and pragmatic perspective.1. Theoretical frameworkDifferent disciplines have been interested into the question of meaning, going from lexicology, semantics, to semiotics, and philosophy of language. Broadly speaking, the context is considered paramount, as Malinowski or Firth put it, for example through the famous quotation of the latter (arguing against structural linguistics) “you shall know a word by the company it keeps” (Firth, 1957). Taken to an extreme, Polguère (2015) calls it ‘lexical contextualism’, a conception that considers that words do not have meaning in the absolute (isolated): it would be their contexts that would bring it. Other less radical positions, such as the Generative Lexicon (Pustejovsky, 1995), suggest that all words have an original meaning. When polysemic, the different meanings derive by inference from an initial (original) meaning, depending on the usage of a word in a precise context. Contextualism, be it radical or moderated, is linked to the notion of ‘semantic potential’ proposed by Recanati (2004), notion that Polguère (ibid.) illustrates with the image of an unlit light bulb: “we should not argue against the fact that words do not ‘mean’ by themselves. They ‘have a meaning’, i.e. an inherent property that conditions their denotational effect in semiosis but considered by itself, a word is just like an unlit light bulb”. Last, but not least, Bakhtine considers the context in light of a dialogism inherent to the lexicon (kind of polyphony): the word “never refers to a single conscience, a single voice. (…) it is received through the voice of someone else” (Bakhtine, [1929] 2001, p. 235‑236).The notion of lexical meaning is at the heart of language learning and it can not be dissociated from the notion of context. As we can see, from contextualism to polyphony, the notion is complex and difficult to grasp. From there, how to facilitate access to meaning while teaching French L1 or L2?2. Pedagogical aspectsTo teach vocabulary (and to facilitate the access to word senses), language teachers can deploy explicit activities, that is specific and systematic exercises on vocabulary (Cellier, 2011). Implicit activities such as oral games, reading aloud, creating mind-maps, etc. to name a few, can also contribute to vocabulary learning. These implicit activities, which vary depending on the learners and on the level of language, have many advantages. A significant number of words are involved in effective classroom communication. In contextualizing them, the teacher can enhance their appropriation (Cellier, 2011). The role of the context is thus paramount. If quantitative approaches are important when learning vocabulary (increasing the lexical stock of the learner), qualitative approaches can not be ignored (Grossmann, 2011). While for a long time, pedagogical practices related to vocabulary have privileged quantitative aspects (word lists are still present in textbooks), a variety of activities are now implemented enabling to develop metalinguistic skills, i.e. getting access to word senses whilst working on contexts. Once again, the role of context is crucial.Recent studies in second language acquisition in general (Meara, 1996; Boulton, 1998) and specifically in French L2 (Cavalla, 2019) show the importance to teach/learn vocabulary in context as to dynamically build a diversified mental lexicon. The point is here to acquire skills and not lexical knowledge (Holec, 1994) to be able to cope with different situations, in comprehension and production.Besides, a variety of activities can be proposed in complement to textbook activities to handle heterogeneous classrooms: getting access to meaning may vary depending on the learner, his/her learning culture, his/her mother tongue (i.e. proximity with the languages already learnt), the languages learnt before, his/her motivation, etc. Insights on translation, cross-comprehension (Caddéo et Jamet, 2013), emotions (Cavalla, 2017), not to mention embodiment (Eshenauer et al., “Encorporer les langues vivantes” article in this issue), may also help memorizing new words and thus vocabulary appropriation. Finally, in communicative approaches for vocabulary teaching in L2, students are encouraged to use language as vehicle of communication and gradually develop their strategies in communication by using authentic texts. Vocabulary comprehension is linked to reflective activities on reading texts in the target language (Riquois, 2020) and on the role of context to infer meaning of unknown words.3. Contents of this articleIn this article, the authors propose different activities set up in French L1 or L2 classrooms, having in common a particular focus on the role of context in the processes of linguistic units’ learning. Following an overview of the domain as regards to its theoretical and educational aspects, we present innovative methods that go beyond more traditional approaches. Being complementary, those different activities are proposed as ‘food for thought’ on the complexity of contextualization for vocabulary appropriation and on the perspectives that contextualization offers on teaching/learning strategies. Considering the above, the authors raise the following question ‘is the process of accessing to meaning (word senses) really different in L1 and L2?’ and, consequently, they invite to rethink the artificial but persistent differentiation between L1 and L2 teaching approaches.

Natural Language Processing (NLP) represents the task of automatic handling of natural human language by machines. There is a large spectrum of possible NLP applications which aid in automating tasks like text translation amongst languages, retrieving and summarizing data from very huge and complex repositories, spam email filtering, identifying fake news in digital media, finding political opinions, views and sentiments of people on various government policies, providing effective medical assistance based on past history records of patients etc. Gujarati language is an Indian language with more than sixty million users worldwide. At present, many efforts are laid for developing NLP applications and resources for Indian languages. This survey gives a taxonomy and comprehensive report regarding component and resource development for Gujarati NLP systems. Also, few prominent tools available in open domain are tested, and their posterior analysis is presented. Possible measures to handle the issues in resource and component development of Gujarati NLP system are also discussed. This report might be useful for industry, researchers and academicians to have a clear picture of the research gaps, challenges and opportunities in Gujarati NLP systems. [ABSTRACT FROM AUTHOR]

This paper gives an overview of the conducted research on Lithuanian multi-word expressions, particularly, collocations, and presents the developed resources. Beginning from the identification, analysis, and lexicographic description of MWEs in general, the focus of the research was narrowed down to collocations and their certain features, such as arbitrariness, during the later stages. Arbitrary collocations were seen as having lexically motivated relations and a certain degree of restricted collocability of constituents. Within the framework of the two projects, PASTOVU (2016-2018) and ARKA (2020-2022), corpus-driven approaches were applied to extract and document Lithuanian collocations and develop a number of lexical resources to be discussed in this paper. [ABSTRACT FROM AUTHOR]

The Romanian WordNet (RoWN) database is an impressive collection of Romanian nouns, verbs, adjectives, and adverbs, which can be seen as a network of nodes where, words can be found in a certain context to have the same meaning, and in the mesh of that network are found the other words that in turn can become a network node for another word in a specific context. In this study we propose an approach for the problem of aligning the word senses form RoWordNet with those of the Thesaurus Dictionary of the Romanian Language in electronic format (eDTLR), by exploiting the collections of definitions and examples in the two linguistic thesauri, based on a statistical model, where four heuristics are proposed for solving this issue. [ABSTRACT FROM AUTHOR]

Copyright of Slavistična Revija is the property of Slavisticno Drustvo Slovenije and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Great efforts are being made to increase the utility of linguistic resources in applications related to language processing by interconnecting them. This study is focused on the Romanian language, which is a young language in this domain, for which it has to be made big steps until it is considered well resourced - both qualitatively and quantitatively. The CoRoLa corpus has been developed for 4 years and since 2017 it is visible for research. It cumulates about one billion words, annotated (tokenized, lemmatized, morphologically and syntactically processed). Other two resources used in this study are the eDTLR (the electronic version of the Thesaurus Dictionary of the Romanian Language) and Romanian WordNet. In this study it is described a technology that unifies these resources and brings them to a common standard, which leads the way for an efficient coupling of these resources. With this new obtained standardized resource, a series of test and case studies were performed, with the benefit of a much more diverse exposure on using the Romanian language. [ABSTRACT FROM AUTHOR]

In the present article we make an effort to develop the ideas of the Russian linguist G.P. Melnikov about the determinants of the language system in the context of his study about the dynamic language nature. The article is devoted to argumentation of peculiarity of multi-structural languages lexical recourses based on their inner form. Significance of the present article is determined, at first, by increased interest from scientists to comparative study of the languages used within one territory in conditions of preservation of their national and cultural originality; second, by insufficient information about linguistic peculiarities of short folklore genre of the Teleut people; third, by scientific relevant tendency to explanatoriness of surveys in the sphere of modern linguistics that is directed to human beings and the world around them. The goal of the authors is to research typical communicatively relevant ways to reflect extralinguistic reality that determine vocabulary of the Russian and Teleut languages. To achieve the stated goal the authors use in the present article data-fetching methods (data from dictionaries, via informants interviewing and questionnaire), descriptions, comparisons, experiments as well as the methods of linguoculturological and statistic analyses. The material for this study is based on proverbs, superstitions, riddles, idioms that are regarded as the elements of the Russian and Teleut people spiritual culture. Communicative aspects of culturally significant facts comprehension identified through lexical universals analyses allow us to define the national world-image of the Russian and Teleut people. The conducted research proved that received during the analyses typical and unique coding methods of the information preserved in the depths of national memory determine lexical originality of compared languages. As a result, the study of paroemiological fund of the Russian and Teleut language that is based on the inner form category allowed the authors of the present article to reveal the mechanism of linguoculturological processes happening between them.

Distributional Semantic Models (DSMs) established themselves as a standard for the representation of word and sentence meaning. However, DSMs provide quantitative measurement of how strongly two linguistic expressions are related, without being able to automatically classify different semantic relations. Hence the notion of semantic similarity is underspecified in DSMs. We introduce Evalution-MAN in this paper as an effort to address this underspecification problem. Following the EVALution 1.0 dataset for English, we present a dataset for evaluating DSMs on the task of the identification of semantic relations in Mandarin Chinese. Moreover, we test different types of word vectors on the automatic learning of these semantic relations, and we evaluate them both in a unsupervised and in a supervised setting, finding that distributional models tend, in general, to assign higher similarity scores to synonyms and that deep learning classifiers are the best performing ones in the identification of semantic relations.

Languages with insufficient digitally available resources, such as, Indian–Indian and English–Indian language Machine Translation (MT) system developments, faces the difficulty to translate various lexical phenomena. In this paper, we present our work on a comparative study of 440 phrase-based statistical trained models for 110 language pairs across 11 Indian languages. We have developed 110 baseline statistical machine translation systems. Then, we have augmented the training corpus with Indowordnet synset word entries of lexical database and further trained 110 models on top of the baseline system. We have done a detailed performance comparison using various evaluation metrics such as BLEU score, METEOR, and TER. We observed significant improvement in evaluations of translation quality across all the 440 models after using the Indowordnet. These experiments give a detailed insight in two ways: (1) usage of lexical database with synset mapping for resource poor languages and (2) efficient usage of Indowordnet synset mapping. Moreover, synset mapped lexical entries helped the SMT system to handle the ambiguity to a great extent during the translation. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Definitional knowledge has proved to be essential in various Natural Language Processing tasks and applications, especially when information at the level of word senses is exploited. However, the few sense-annotated corpora of textual definitions available to date are of limited size: this is mainly due to the expensive and time-consuming process of annotating a wide variety of word senses and entity mentions at a reasonably high scale. In this paper we present SenseDefs, a large-scale high-quality corpus of disambiguated definitions (or glosses) in multiple languages, comprising sense annotations of both concepts and named entities from a wide-coverage unified sense inventory. Our approach for the construction and disambiguation of this corpus builds upon the structure of a large multilingual semantic network and a state-of-the-art disambiguation system: first, we gather complementary information of equivalent definitions across different languages to provide context for disambiguation; then we refine the disambiguation output with a distributional approach based on semantic similarity. As a result, we obtain a multilingual corpus of textual definitions featuring over 38 million definitions in 263 languages, and we publicly release it to the research community. We assess the quality of SenseDefs's sense annotations both intrinsically and extrinsically on Open Information Extraction and Sense Clustering tasks. [ABSTRACT FROM AUTHOR]

This study aims to construct a corpus-informed list of Arabic Formulaic Sequences (ArFSs) for use in language pedagogy (LP) and Natural Language Processing (NLP) applications. A hybrid mixed methods model was adopted for extracting ArFSs from a corpus, that combined automatic and manual extracting methods, based on well-established quantitative and qualitative criteria that are relevant from the perspective of LP and NLP. The pedagogical implications of this list are examined to facilitate the inclusion of ArFSs in the process of learning and teaching Arabic, particularly for non-native speakers. The computational implications of the ArFSs list are related to the key role of the ArFSs as a novel language resource in the improvement of various Arabic NLP tasks. [ABSTRACT FROM AUTHOR]

Lexical platform – the first step towards user-centred integration of lexical resources Lexical platform – the first step towards user-centred integration of lexical resources The paper describes the Lexical Platform - a means for lightweight integration of independent lexical resources. Lexical resources (LRs) are represented as web components that implement a minimal set of predefined programming interfaces. These provide functionality for querying and generate a simple, common presentation format. Therefore, a common data format is not needed and the identity of component LRs is preserved. Users can search, browse and navigate via resources on the basis of a limited set of anchor elements such as base form, word form and synset id. Platforma leksykalna – pierwszy krok w kierunku integracji zasobów leksykalnych zorientowanej na użytkowników Artykuł opisuje Platformę Leksykalną – sposób na lekką integrację niezależnych zasobów leksykalnych. Zasoby leksykalne są na niej reprezentowane jako komponenty webowe, które implementują minimalny zestaw predefiniowanych interfejsów programistycznych. Interfejsy te dostarczają funkcjonalność do przeszukiwania oraz generują prosty, jednolity format prezentacji zasobów. W związku z tym wspólny format danych nie jest konieczny i tożsamość składowych zasobów leksykalnych jest zachowana. Użytkownicy mogą przeszukiwać zasoby na podstawie ograniczonego zbioru odwołań takich jak forma podstawowa, forma wyrazowa i identyfikator synsetu.

Lexical resources are fundamental to tackle many tasks that are central to present and prospective research in Text Mining, Information Retrieval, and connected to Natural Language Processing. In this article we introduce COVER, a novel lexical resource, along with COVERAGE, the algorithm devised to build it. In order to describe concepts, COVER proposes a compact vectorial representation that combines the lexicographic precision characterizing BabelNet and the rich common-sense knowledge featuring ConceptNet. We propose COVER as a reliable and mature resource, that has been employed in as diverse tasks as conceptual categorization, keywords extraction, and conceptual similarity. The experimental assessment is performed on the last task: we report and discuss the obtained results, pointing out future improvements. We conclude that COVER can be directly exploited to build applications, and coupled with existing resources, as well. [ABSTRACT FROM AUTHOR]

Orthography-semantics consistency (OSC) is a measure that quantifies the degree of semantic relatedness between a word and its orthographic relatives. OSC is computed as the frequency-weighted average semantic similarity between the meaning of a given word and the meanings of all the words containing that very same orthographic string, as captured by distributional semantic models. We present a resource including optimized estimates of OSC for 15,017 English words. In a series of analyses, we provide a progressive optimization of the OSC variable. We show that computing OSC from word-embeddings models (in place of traditional count models), limiting preprocessing of the corpus used for inducing semantic vectors (in particular, avoiding part-of-speech tagging and lemmatization), and relying on a wider pool of orthographic relatives provide better performance for the measure in a lexical-processing task. We further show that OSC is an important and significant predictor of reaction times in visual word recognition and word naming, one that correlates only weakly with other psycholinguistic variables (e.g., family size, word frequency), indicating that it captures a novel source of variance in lexical access. Finally, some theoretical and methodological implications are discussed of adopting OSC as one of the predictors of reaction times in studies of visual word recognition. [ABSTRACT FROM AUTHOR]

The paper describes the Lexical Platform -- a means for lightweight integration of independent lexical resources. Lexical resources (LRs) are represented as web components that implement a minimal set of predefined programming interfaces. These provide functionality for querying and generate a simple, common presentation format. Therefore, a common data format is not needed and the identity of component LRs is preserved. Users can search, browse and navigate via resources on the basis of a limited set of anchor elements such as base form, word form and synset id. [ABSTRACT FROM AUTHOR]