MWU-aware Part-of-Speech Tagging with a CRF model and lexical resources

Mathieu Constant (1) , Anthony Sigogne (1)

1 LIGM - Laboratoire d'Informatique Gaspard-Monge

This paper describes a new part-of-speech tagger including multiword unit (MWU) identification. It is based on a Conditional Random Field model integrating language-independent features, as well as features computed from external lexical resources. It was implemented in a finite-state framework composed of a preliminary finite-state lexical analysis and a CRF decoding using weighted finite-state transducer composition. We showed that our tagger reaches state-of-the-art results for French in the standard evaluation conditions (i.e. each multiword unit is already merged in a single token). The evaluation of the tagger integrating MWU recognition clearly shows the interest of incorporating features based on MWU resources.

Domains: Computation and Language [cs.CL]

Mathieu Constant, Anthony Sigogne. MWU-aware Part-of-Speech Tagging with a CRF model and lexical resources. ACL Workshop on Multiword Expressions: from Parsing and Generation to the Real World (MWE'11), 2011, Portland, Oregon, United States. pp.49-56. ⟨hal-00621585⟩