Sources of Complexity in Semantic Frame Parsing for Information Extraction

Abstract : This paper describes a Semantic Frame parsing System based on sequence labeling methods, precisely BiLSTM models with highway connections, for performing information extraction on a corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism. The approach proposed in this study relies on an integrated sequence labeling model which jointly optimizes frame identification and semantic role segmentation and identification. The purpose of this study is to analyze the task complexity, to highlight the factors that make Semantic Frame parsing a difficult task and to provide detailed evaluations of the performance on different types of frames and sentences.
Type de document :
Communication dans un congrès
International FrameNet Workshop 2018, May 2018, Miyazaki, Japan
Liste complète des métadonnées

Littérature citée [5 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01731385
Contributeur : Frederic Bechet <>
Soumis le : mercredi 14 mars 2018 - 10:51:31
Dernière modification le : jeudi 5 avril 2018 - 01:31:09
Document(s) archivé(s) le : vendredi 15 juin 2018 - 13:39:03

Fichier

sources-complexity-semantic.pd...
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01731385, version 1

Collections

Citation

Gabriel Marzinotto, Frédéric Béchet, Géraldine Damnati, Alexis Nasr. Sources of Complexity in Semantic Frame Parsing for Information Extraction. International FrameNet Workshop 2018, May 2018, Miyazaki, Japan. 〈hal-01731385〉

Partager

Métriques

Consultations de la notice

119

Téléchargements de fichiers

58