Towards a DRS Parsing Framework for French

Luyen Le Ngoc (1, 2) , Yannis Haralambous (3, 1) , Philippe Lenca (3, 4)

1 IMT Atlantique - INFO - Département Informatique
2 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_IMTA_CID_DECIDE
4 IMT Atlantique - LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information

Combinatory Categorial Grammars provide a transparent interface between surface syntax and underlying semantic representation. Discourse Representation Theory allows the handling of meaning across sentence boundaries. Based on the foundations of these two theories along with the work of Johan Bos on the Boxer framework for English language, we propose an approach to the task of semantic parsing with Discourse Representation Structure for the French language. By giving an example of discourse analysis on French sentences and experimenting on 4,525 sentences taken from the French Treebank corpus, we demonstrate and evaluate the outcomes of our framework.

Mots clés: Semantic parsing; Discourse representation theory; Combinatory categorial grammars; Boxer; French language

Domaines: Interface homme-machine [cs.HC]; Traitement du texte et du document; Ordinateur et société [cs.CY]; Réseaux et télécommunications [cs.NI]; Intelligence artificielle [cs.AI]; Linguistique

Luyen Le Ngoc, Yannis Haralambous, Philippe Lenca. Towards a DRS Parsing Framework for French. SNAMS 2019 : Sixth International Conference on Social Networks Analysis, Management and Security, Oct 2019, Granada, Spain. ⟨10.1109/SNAMS.2019.8931868⟩. ⟨hal-02280800⟩