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Extraction of Lexico-Syntactic Information and Acquisition of Causality Schemas for Text Annotation

Laurent Alamarguy Rose Dieng-Kuntz Catherine Faron Zucker 1, 2 
2 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : We present the INSYSE method for the annotation of texts, based on extraction of semantic relations from syntactic structures. We apply this method to a corpus of 5000 Medline abstracts about central nervous system diseases and gene interactions. Our cooperative approach focuses on (1) extracting lexico-syntactic information from sentences in the corpus comprising causation lexemes and (2) elaborating unification grammar rules which enable to extract instantiated conceptual schemas from this information. They are translated into RDF annotations which used by the semantic search engine Corese to query the corpus about functions of genes and their correlations with particular diseases.
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Submitted on : Wednesday, January 5, 2022 - 3:40:42 PM
Last modification on : Thursday, August 4, 2022 - 4:55:01 PM
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Laurent Alamarguy, Rose Dieng-Kuntz, Catherine Faron Zucker. Extraction of Lexico-Syntactic Information and Acquisition of Causality Schemas for Text Annotation. 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, Sep 2005, Melbourne, Australia. pp.1180 - 1186, ⟨10.1007/11553939_164⟩. ⟨hal-03503001⟩



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