Paper: Tree Representations in Probabilistic Models for Extended Named Entities Detection

ACL ID E12-1018
Title Tree Representations in Probabilistic Models for Extended Named Entities Detection
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

In this paper we deal with Named En- tity Recognition (NER) on transcriptions of French broadcast data. Two aspects make the task more difficult with respect to previ- ous NER tasks: i) named entities annotated used in this work have a tree structure, thus the task cannot be tackled as a sequence la- belling task; ii) the data used are more noisy than data used for previous NER tasks. We approach the task in two steps, involving Conditional Random Fields and Probabilis- tic Context-Free Grammars, integrated in a single parsing algorithm. We analyse the effect of using several tree representations. Our system outperforms the best system of the evaluation campaign by a significant margin.