Semantic Roles in Valency Lexicon of Czech Verbs: Verbs of Communication and Exchange

Kettnerová, Václava; Lopatková, Markéta; Hrstková, Klára

doi:10.1007/978-3-540-85287-2_21

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Vallex provides semantic class membership [8] and valency patterns for all meanings (i.e. lexical units) of verbs included and it was the reason why Vallex was chosen as the base for the NomVallex project.…”

Section: The Development Of Nomvallexmentioning

confidence: 99%

Possible but not probable :A quantitative analysis of valency behaviour of Czech nouns in the Prague Dependency Treebank

Kolářová

Vernerová

Klímová

et al. 2017

Journal of Linguistics/Jazykovedný Casopis

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Abstract:In order to optimize corpus searches for valency lexicon production, we analyse the relative frequencies of different combinations of valency complementations of Czech deverbal nouns in the Prague Dependency Treebank, considering differences between productively and non-productively derived nouns and their semantic class. We also classify combinations of forms of participants according to their frequency.

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Section: The Development Of Nomvallexmentioning

confidence: 99%

Possible but not probable :A quantitative analysis of valency behaviour of Czech nouns in the Prague Dependency Treebank

Kolářová

Vernerová

Klímová

et al. 2017

Journal of Linguistics/Jazykovedný Casopis

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“…nouns, verbs or adjectives. However, most valency dictionaries focus primarily on verbs [10][11][12][13][14][15]. Verbs can be selected quantitatively, because of their high ranking in the frequency list of general reference corpora, or qualitatively, depending on their semantic field…”

Section: Figure1 Verb Entry In a Valency Arabic Lexiconmentioning

confidence: 99%

A Corpus-based Arabic Valency Dictionary: The Case of Fighting Verbs

Abdelzaher

Elghamry

Elattar

2017

The Egyptian Journal of Language Engineering

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Empirical pedagogical dictionaries aim at defining words in their context and presenting corpus-based evidence for each word. They are meant to teach language learners how to use a word correctly. Valency, which describes the arguments of a verb syntactically and semantically, is of unique importance to pedagogical dictionaries. Unfortunately, Arabic lacks corpus-based valency resources. Thus, this paper proposes a monolingual corpus-based valency dictionary, for Arabic learners, covering fighting verbs. The dictionary explores the valency of fighting verbs in Sketch Engine's uploaded Arabic TenTen corpus. The dictionary compiling method depends on both automatic word sketch function to identify the lexico-syntactic patterns of verbs and on threelayer manual annotation of corpus-driven examples to consolidate the results. Each verb entry, in the dictionary, displays (a) number; (b) phrase type; (c) semantic role; (d) grammatical function of its arguments and (e) definition of its different senses. At least, three annotated examples are provided for each verb sense to illustrate its usage authentically. The dictionary, integrating semantic and syntactic information, facilitates effective learning of new Arabic vocabulary.

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“…Knowledge acquisition in FN is a manual process of grouping words with semantic overlap according to some explicit criteria to form frames and sentence annotation based on multiple annotation layers (Kettnerová et al, 2008). The annotation process involves FN lexicographers to declare each word in a sentence as a target, then select a frame related to the target, get a set of annotation layers and appropriate frame element tags and the annotate the relevant constituents (Ruppenhofer et al, 2006).…”

Section: Framenetmentioning

confidence: 99%

Towards knowledge modeling and manipulation technologies: A survey

Bimba

Al-Hunaiyyan

Mahmud

et al. 2016

International Journal of Information Management

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A system which represents knowledge is normally referred to as a knowledge based system (KBS). This article focuses on surveying publications related to knowledge base modelling and manipulation technologies, between the years 2000-2015. A total of 185 articles excluding the subject descriptive articles which are mentioned in the introductory parts, were evaluated in this survey. The main aim of this study is to identify different knowledge base modelling and manipulation techniques based on 4 categories; 1) linguistic knowledge base; 2) expert knowledge base; 3) ontology and 4) cognitive knowledge base. This led to the proposition of 8 research questions, which focused on the different categories of knowledge base modelling technologies, their underlying theories, knowledge representation technique, knowledge acquisition technique, challenges, applications, development tools and development languages. A part of the findings from this survey is the high dependence of linguistic knowledge base, expert knowledge base and ontology on volatile expert knowledge. A promising technique for knowledge-based business management and other knowledge related applications is also discussed.

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Semantic Roles in Valency Lexicon of Czech Verbs: Verbs of Communication and Exchange

Cited by 3 publications

References 2 publications

Possible but not probable :A quantitative analysis of valency behaviour of Czech nouns in the Prague Dependency Treebank

Possible but not probable :A quantitative analysis of valency behaviour of Czech nouns in the Prague Dependency Treebank

A Corpus-based Arabic Valency Dictionary: The Case of Fighting Verbs

Towards knowledge modeling and manipulation technologies: A survey

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