ZORE: A Syntax-based System for Chinese Open Relation Extraction

Open Relation Extraction (ORE) overcomes the limitations of traditional IE techniques, which train individual extractors for every single relation type. Systems such as ReVerb, PATTY, OLLIE, and Exemplar have attracted much attention on English ORE. However, few studies have been reported on ORE for languages beyond English. This paper presents a syntax-based Chinese (Zh) ORE system, ZORE, for extracting relations and semantic patterns from Chinese text. ZORE identifies relation candidates from automatically parsed dependency trees, and then extracts relations with their semantic patterns iteratively through a novel double propagation algorithm. Empirical results on two data sets show the effectiveness of the proposed system.

[1]  Denilson Barbosa,et al.  Effectiveness and Efficiency of Open Relation Extraction , 2013, EMNLP.

[2]  M. A. R T A P A L,et al.  The Penn Chinese TreeBank: Phrase structure annotation of a large corpus , 2005, Natural Language Engineering.

[3]  Oren Etzioni,et al.  Open Information Extraction from the Web , 2007, CACM.

[4]  Oren Etzioni,et al.  Identifying Relations for Open Information Extraction , 2011, EMNLP.

[5]  Wanxiang Che,et al.  LTP: A Chinese Language Technology Platform , 2010, COLING.

[6]  Ralph Grishman,et al.  Automatic Acquisition of Domain Knowledge for Information Extraction , 2000, COLING.

[7]  Stephen Clark,et al.  Syntactic Processing Using the Generalized Perceptron and Beam Search , 2011, CL.

[8]  Dan I. Moldovan,et al.  Acquisition of semantic patterns for information extraction from corpora , 1993, Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications.

[9]  Oren Etzioni,et al.  Open Language Learning for Information Extraction , 2012, EMNLP.

[10]  Dandan Liu,et al.  Incorporating Lexical Semantic Similarity to Tree Kernel-Based Chinese Relation Extraction , 2012, CLSW.

[11]  Peng Jin,et al.  Multi-view Chinese Treebanking , 2014, COLING.

[12]  Christopher D. Manning,et al.  Optimizing Chinese Word Segmentation for Machine Translation Performance , 2008, WMT@ACL.

[13]  Denilson Barbosa,et al.  Open Information Extraction with Tree Kernels , 2013, NAACL.

[14]  Richard Johansson,et al.  Dependency-based Semantic Role Labeling of PropBank , 2008, EMNLP.

[15]  Oren Etzioni,et al.  Open Information Extraction: The Second Generation , 2011, IJCAI.

[16]  Wanxiang Che,et al.  Improved-Edit-Distance Kernel for Chinese Relation Extraction , 2005, IJCNLP.

[17]  Regina Barzilay,et al.  Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment , 2003, NAACL.

[18]  Daniel S. Weld,et al.  Open Information Extraction Using Wikipedia , 2010, ACL.

[19]  Jian Su,et al.  A Composite Kernel to Extract Relations between Entities with Both Flat and Structured Features , 2006, ACL.

[20]  Oren Etzioni,et al.  Chinese Open Relation Extraction for Knowledge Acquisition , 2014, EACL.

[21]  Likun Qiu,et al.  Combining Contextual and Structural Information for Supersense Tagging of Chinese Unknown Words , 2011, CICLing.

[22]  Oren Etzioni,et al.  A Latent Dirichlet Allocation Method for Selectional Preferences , 2010, ACL.

[23]  Jian Su,et al.  Exploring Various Knowledge in Relation Extraction , 2005, ACL.

[24]  Daniel Jurafsky,et al.  Discriminative Reordering with Chinese Grammatical Relations Features , 2009, SSST@HLT-NAACL.

[25]  J. Allan,et al.  On-Line New Event Detection using Single Pass Clustering , 1998 .

[26]  Denilson Barbosa,et al.  Extracting information networks from the blogosphere , 2012, TWEB.

[27]  Miriam Butt The Light Verb Jungle , 2003 .

[28]  Roberto Navigli,et al.  WiSeNet: building a wikipedia-based semantic network with ontologized relations , 2012, CIKM '12.

[29]  Furu Wei,et al.  A Novel Feature-based Approach to Chinese Entity Relation Extraction , 2008, ACL.

[30]  Gerhard Weikum,et al.  PATTY: A Taxonomy of Relational Patterns with Semantic Types , 2012, EMNLP.

[31]  Roberto Navigli,et al.  Integrating Syntactic and Semantic Analysis into the Open Information Extraction Paradigm , 2013, IJCAI.