Paper: Knowledge Extraction From Texts: A Method For Extracting Predicate-Argument Structures From Texts

ACL ID C94-2168
Title Knowledge Extraction From Texts: A Method For Extracting Predicate-Argument Structures From Texts
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1994
Authors
  • Florence Pugeault (CNRS, France; Institute of Research in Informatics Toulouse, Toulouse France; University of Toulouse 3, Toulouse France; Electricity of France (EDF) Research Center, France)
  • Patrick Saint-Dizier (CNRS, France; Institute of Research in Informatics Toulouse, Toulouse France; University of Toulouse 3, Toulouse France)
  • Marie-Gaelle Monteil (Electricity of France (EDF) Research Center, France)

loc). prep: dans, surr de, etc. proper noun I profession. animate F, xamples d6finir, repr6senter, cr6er, r6aliser, continuer, poursuivre, aider, collaborer, donner, 6ch,angcr, rechercher, r6soudr G etc. vouloir, d6sirer, devoir, obliger, ndcessiter. favoriser, pennettre, conduire, ddcider, diriger, mener. savoil) connaitre. 6tcndre, poursuivre, explorer, observer, devoir, obliger, donner, 6changer, attacher, c!lahmr, etc. conslruire, r6aliser utiliser, SP6cifier (par). aller, venir, attacher, chalner, relier (h). baplJser, nommer. collaborer, participer, attaching prep: avec attacher (ave@, unir. Sample of the organization of thematic roles w.r.p, to semantic classes of verbs, selectional restrictions and prepositions. 1043