Enriching the "Senso Comune" Platform with Automatically Acquired Data

• Main Authors: Caselli, Tommaso, Vieu, Laure, Strapparava, Carlo, Vetere, Guido
• Other Authors: Università degli Studi di Trento = University of Trento (UNITN), MEthodes et ingénierie des Langues, des Ontologies et du DIscours (IRIT-MELODI), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Laboratory for Applied Ontology (LOA), Istituto di Scienze e Tecnologie della Cognizione Trento (ISTC-CNR), Centre National de la Recherche Scientifique (CNRS), Fondazione Bruno Kessler Trento, Italy (FBK), IBM Roma
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2014
• Subjects: Word Sense Alignment; Verb Frame Acquisition; Lexico-semantic Resource; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]; Iceland
• Online Access: https://hal.science/hal-01138072; https://hal.science/hal-01138072/document; https://hal.science/hal-01138072/file/Caselli_13177.pdf

International audience This paper reports on research activities on automatic methods for the enrichment of the Senso Comune platform. At this stage of development, we will report on two tasks, namely word sense alignment with MultiWordNet and automatic acquisition of Verb Shallow Frames from sense annotated data in the MultiSemCor corpus. The results obtained are satisfying. We achieved a final F-measure of 0.64 for noun sense alignment and a F-measure of 0.47 for verb sense alignment, and an accuracy of 68% on the acquisition of VerbShallow Frames.