Parenthetical Classification for Information Extraction - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Parenthetical Classification for Information Extraction

Résumé

The article focuses on a rather unexplored topic in NLP: parenthetical classification. Parentheticals are defined as any text sequence between parentheses. They have been approached from isolated perspectives, like translation pairs extraction, but a full account of their syntactic and semantic properties is lacking. This article proposes a new comprehensive scheme drawn from corpus-based linguistic studies on French news. This research is part of a project investigating the structural aspects of punctuation signs and their usefulness for Information Extraction. Parenthetical classification is approached as a relation extraction problem split into three correlated subtasks: syntactic and semantic classification and head recognition. Corpus-based studies singled out 11 syntactic and 18 semantic relation subtypes. The article addresses automatic classification, using a combination of CRF and SVM. This baseline system reports 0.674 (head recognition), 0.908 (syntax), 0.734 (semantics), and 0.518 (end-to-end) of F1.
Fichier principal
Vignette du fichier
coling2012_11_04.pdf (131.38 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00768590 , version 1 (22-12-2012)

Identifiants

  • HAL Id : hal-00768590 , version 1

Citer

Ismaïl El Maarouf, Jeanne Villaneau. Parenthetical Classification for Information Extraction. COLING 2012, Dec 2012, Mumbai, India. pp.297--308. ⟨hal-00768590⟩
305 Consultations
95 Téléchargements

Partager

Gmail Facebook X LinkedIn More