title: ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering.
abstract: Entity recognition is an important but challenging research problem. In reality, many text collections are from specific, dynamic, or emerging domains, which poses significant new challenges for entity recognition with increase in name ambiguity and context sparsity, requiring entity detection without domain restriction. In this paper, we investigate entity recognition (ER) with distant-supervision and propose a novel relation phrase-based ER framework, calledClusType, that runsdata-drivenphrase mining to generate entity mention candidates and relation phrases, and enforces the principle that relation phrases should besoftlyclustered when propagating type information between their argument entities. Then we predict the type ofeachentity mention based on the type signatures of its co-occurring relation phrases and the type indicators of its surface name, as computed over the corpus. Specifically, we formulate a joint optimization problem for two tasks,type propagation with relation phrasesandmulti-view relation phrase clustering. Our experiments on multiple genres-news, Yelp reviews and tweets-demonstrate the effectiveness and robustness of ClusType, with an average of 37% improvement in F1 score over the best compared method.
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, IL, USA.
authors.forename: Xiang
authors.initials: X
authors.lastname: Ren
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, IL, USA.
authors.forename: Ahmed
authors.initials: A
authors.lastname: El-Kishky
authors.affiliation: Microsoft Research, Redmond, WA, USA.
authors.forename: Chi
authors.initials: C
authors.lastname: Wang
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, IL, USA.
authors.forename: Fangbo
authors.initials: F
authors.lastname: Tao
authors.affiliation: Information Sciences Directorate, Army Research Laboratory, Adelphi, MD, USA.
authors.forename: Clare R
authors.initials: CR
authors.lastname: Voss
authors.affiliation: Computer Science Department, Rensselaer Polytechnic Institute, USA.
authors.forename: Heng
authors.initials: H
authors.lastname: Ji
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, IL, USA.
authors.forename: Jiawei
authors.initials: J
authors.lastname: Han
keywords: Entity Recognition and Typing; Relation Phrase Clustering