Title :

A Framework for Understanding the Role of Morphology in Universal Dependency Parsing

Author(s) :

Dehouck, Mathieu [Auteur]
Machine Learning in Information Networks [MAGNET]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Denis, Pascal [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Machine Learning in Information Networks [MAGNET]

Conference title :

EMNLP 2018 - Conference on Empirical Methods in Natural Language Processing

City :

Brussels

Country :

Belgique

Start date of the conference :

2018-10-31

Journal title :

Proceedings of EMNLP 2018

HAL domain(s) :

Informatique [cs]/Informatique et langage [cs.CL]
Informatique [cs]/Apprentissage [cs.LG]
Informatique [cs]/Traitement du texte et du document
Sciences de l'Homme et Société/Linguistique

English abstract : [en]

This paper presents a simple framework forcharacterizing morphological complexity andhow it encodes syntactic information. In particular,we propose a new measure of morphosyntacticcomplexity in terms of governordependent ...
Show more >This paper presents a simple framework forcharacterizing morphological complexity andhow it encodes syntactic information. In particular,we propose a new measure of morphosyntacticcomplexity in terms of governordependentpreferential attachment that explainsparsing performance. Through experimentson dependency parsing with datafrom Universal Dependencies (UD), we showthat representations derived from morphologicalattributes deliver important parsing performanceimprovements over standard wordform embeddings when trained on the samedatasets. We also show that the new morphosyntacticcomplexity measure is predictive ofthe gains provided by using morphological attributesover plain forms on parsing scores,making it a tool to distinguish languages usingmorphology as a syntactic marker from others.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL