Paper: Joint Inference of Named Entity Recognition and Normalization for Tweets

ACL ID P12-1055
Title Joint Inference of Named Entity Recognition and Normalization for Tweets
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

Tweets represent a critical source of fresh in- formation, in which named entities occur fre- quently with rich variations. We study the problem of named entity normalization (NEN) for tweets. Two main challenges are the er- rors propagated from named entity recogni- tion (NER) and the dearth of information in a single tweet. We propose a novel graphi- cal model to simultaneously conduct NER and NEN on multiple tweets to address these chal- lenges. Particularly, our model introduces a binary random variable for each pair of words with the same lemma across similar tweets, whose value indicates whether the two related words are mentions of the same entity. We evaluate our method on a manually annotated data set, and show that our method outper- forms the baseline that handles these two task...