Automatic Verbalisation of Biological Events

Bikash Gyawali 1 Claire Gardent 1 Christophe Cerisara 1
1 SYNALP - Natural Language Processing : representations, inference and semantics
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : We present a method for automatically generating descriptions of biological events encoded in the KB BIO 101 Knowledge base. In this knowledge base, events are concepts (e.g., RELEASE) related by role relations (e.g., AGENT, PATIENT, PATH, INSTRUMENT) to the concepts denoting their arguments (e.g., GATED-CHANNEL, VASCULAR-TISSUE, IRON). We propose a probabilistic, unsupervised method which extracts possible verbalisation frames from large biology specific domain corpora and uses probabilities both to select an appropriate frame given an event description and to determine the mapping between syntactic and semantic arguments. That is, probabilities are used to determine which event argument fills which syntactic function (e.g., subject, object) in the produced verbalisation. We evaluate our approach on a corpus of 336 event descriptions, provide a qualitative and quantitative analysis of the results obtained and discuss possible directions for further work.
Type de document :
Communication dans un congrès
International Workshop on Definitions in Ontologies (IWOOD 2015), Jul 2015, Lisbon, Portugal. 2015
Liste complète des métadonnées

Littérature citée [29 références]  Voir  Masquer  Télécharger
Contributeur : Gyawali Bikash <>
Soumis le : lundi 12 octobre 2015 - 15:23:55
Dernière modification le : mardi 18 décembre 2018 - 16:38:01
Document(s) archivé(s) le : jeudi 27 avril 2017 - 00:21:00


Fichiers produits par l'(les) auteur(s)


  • HAL Id : hal-01214569, version 1



Bikash Gyawali, Claire Gardent, Christophe Cerisara. Automatic Verbalisation of Biological Events. International Workshop on Definitions in Ontologies (IWOOD 2015), Jul 2015, Lisbon, Portugal. 2015. 〈hal-01214569〉



Consultations de la notice


Téléchargements de fichiers