Matches in ScholarlyData for { ?s ?p ?o. }
- 741 keyword "Standards for LRs".
- 741 title "Methodologies for Designing and Recording Speech Databases for Corpus Based Synthesis".
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- item-1 hasContent luis-oliveira.
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- item-2 hasContent sergio-paulo.
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- item-3 hasContent luis-figueira.
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- item-4 hasContent carlos-mendes.
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- item-5 hasContent ana-nunes.
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- item-6 hasContent joaquim-godinho.
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- 742 creator stephan-walter.
- 742 type InProceedings.
- 742 label "Linguistic Description and Automatic Extraction of Definitions from German Court Decisions".
- 742 sameAs 742.
- 742 abstract "This paper discusses the use of computational linguistic technology to extract definitions from a large corpus of German court decisions. We present a corpus-based survey of definition structures used in this kind of document. We then evaluate the results of a definition extraction system that uses patterns identified in this survey to extract from dependency parsed text. We show how an automatically induced ranking function improves the quality of the search results of this system, and we discuss methods for the acquisition of further extraction rules.".
- 742 hasAuthorList authorList.
- 742 hasTopic Linguistics.
- 742 isPartOf proceedings.
- 742 keyword "Corpus (creation, annotation, etc.)".
- 742 keyword "Evaluation methodologies".
- 742 keyword "Information Extraction, Information Retrieval".
- 742 title "Linguistic Description and Automatic Extraction of Definitions from German Court Decisions".
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- item-1 hasContent stephan-walter.
- 743 creator beatrice-daille.
- 743 creator lorraine-goeuriot.
- 743 creator natalia-grabar.
- 743 type InProceedings.
- 743 label "Characterization of Scientific and Popular Science Discourse in French, Japanese and Russian".
- 743 sameAs 743.
- 743 abstract "We aim to characterize the comparability of corpora, we address this issue in the trilingual context through the distinction of expert and non expert documents. We work separately with corpora composed of documents from the medical domain in three languages (French, Japanese and Russian) which present an important linguistic distance between them. In our approach, documents are characterized in each language by their topic and by a discursive typology positioned at three levels of document analysis: structural, modal and lexical. The document typology is implemented with two learning algorithms (SVMlight and C4.5). Evaluation of results shows that the proposed discursive typology can be transposed from one language to another, as it indeed allows to distinguish the two aimed discourses (science and popular science). However, we observe that performances vary a lot according to languages, algorithms and types of discursive characteristics.".
- 743 hasAuthorList authorList.
- 743 hasTopic Linguistics.
- 743 isPartOf proceedings.
- 743 keyword "Corpus (creation, annotation, etc.)".
- 743 keyword "Information Extraction, Information Retrieval".
- 743 keyword "Multilinguality".
- 743 title "Characterization of Scientific and Popular Science Discourse in French, Japanese and Russian".
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- item-1 hasContent lorraine-goeuriot.
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- item-2 hasContent natalia-grabar.
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- item-3 hasContent beatrice-daille.
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- 746 creator karel-pala.
- 746 creator lukas-svoboda.
- 746 creator pavel-smerk.
- 746 type InProceedings.
- 746 label "Czech MWE Database".
- 746 sameAs 746.
- 746 abstract "In this paper we deal with a recently developed large Czech MWE database containing at the moment 160,000 MWEs (treated as lexical units). It was compiled from various resources such as encyclopedias and dictionaries, public databases of proper names and toponyms, collocations obtained from Czech WordNet, lists of botanical and zoological terms and others. We describe the structure of the database and compare the built MWEs database with the corpus data from Czech National Corpus SYN2000 (approx. 100 mil. tokens) and present results of this comparison in the paper. These MWEs have not been obtained from the corpus since their frequencies in it are rather low. To obtain a more complete list of MWEs we propose and use a technique exploiting the Word Sketch Engine, which allows us to work with statistical parameters such as frequency of MWEs and their components as well as with the salience for the whole MWEs. We also discuss exploitation of the database for working out a more adequate tagging and lemmatization. The final goal is to be able to recognize MWEs in corpus text and lemmatize them as complete lexical units, i.e. to make tagging and lemmatization more adequate.".
- 746 hasAuthorList authorList.
- 746 hasTopic Linguistics.
- 746 isPartOf proceedings.
- 746 keyword "Corpus (creation, annotation, etc.)".
- 746 keyword "Lexicon, lexical database".
- 746 keyword "MultiWord Expressions & Collocations".
- 746 title "Czech MWE Database".
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