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Conference Papers Year : 2022

Relation Extraction from Clinical Cases for a Knowledge Graph

Extraction de relations dans des cas cliniques pour des graphes de connaissances

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Abstract

We describe a system for automatic extraction of semantic relations between entities in a medical corpus of clinical cases. It builds upon a previously developed module for entity extraction and upon a morphosyntactic parser. It uses experimentally designed rules based on syntactic dependencies and trigger words, as well as on sequencing and nesting of entities of particular types. The results obtained on a small corpus are promising. Our larger perspective is transforming information extracted from medical texts into knowledge graphs.
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Dates and versions

hal-03877015 , version 1 (29-11-2022)

Identifiers

Cite

Agata Savary, Alena Silvanovich, Anne-Lyse Minard, Nicolas Hiot, Mirian Halfeld Ferrari. Relation Extraction from Clinical Cases for a Knowledge Graph. DOING@ADBIS, Sep 2022, Torino, Italy, France. pp.353-365, ⟨10.1007/978-3-031-15743-1_33⟩. ⟨hal-03877015⟩
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