PATTY: A Taxonomy of Relational Patterns with Semantic Types

This paper presents PATTY: a large resource for textual patterns that denote binary relations between entities. The patterns are semantically typed and organized into a subsumption taxonomy. The PATTY system is based on efficient algorithms for frequent itemset mining and can process Web-scale corpora. It harnesses the rich type system and entity population of large knowledge bases. The PATTY taxonomy comprises 350,569 pattern synsets. Random-sampling-based evaluation shows a pattern accuracy of 84.7%. PATTY has 8,162 subsumptions, with a random-sampling-based precision of 75%. The PATTY resource is freely available for interactive access and download.

[1]  Christopher D. Manning,et al.  Generating Typed Dependency Parses from Phrase Structure Parses , 2006, LREC.

[2]  Daniel S. Weld,et al.  Automatically refining the wikipedia infobox ontology , 2008, WWW.

[3]  Gerhard Weikum,et al.  WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .

[4]  Michael Strube,et al.  WikiNet: A Very Large Scale Multi-Lingual Concept Network , 2010, LREC.

[5]  Dekang Lin,et al.  DIRT – Discovery of Inference Rules from Text , 2001 .

[6]  Neville Ryant,et al.  A large-scale classification of English verbs , 2008, Lang. Resour. Evaluation.

[7]  Daniel S. Weld,et al.  Learning 5000 Relational Extractors , 2010, ACL.

[8]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[9]  Haixun Wang,et al.  Towards a Probabilistic Taxonomy of Many Concepts , 2011 .

[10]  Bo Zhang,et al.  StatSnowball: a statistical approach to extracting entity relationships , 2009, WWW '09.

[11]  Ramakrishnan Srikant,et al.  Mining Sequential Patterns: Generalizations and Performance Improvements , 1996, EDBT.

[12]  Ion Androutsopoulos,et al.  A Survey of Paraphrasing and Textual Entailment Methods , 2009, J. Artif. Intell. Res..

[13]  Masaki Murata,et al.  Large-Scale Verb Entailment Acquisition from the Web , 2009, EMNLP.

[14]  Gerhard Weikum,et al.  YAGO2: exploring and querying world knowledge in time, space, context, and many languages , 2011, WWW.

[15]  Ido Dagan,et al.  Global Learning of Typed Entailment Rules , 2011, ACL.

[16]  Marius Pasca,et al.  Latent Variable Models of Concept-Attribute Attachment , 2009, ACL/IJCNLP.

[17]  Catherine Havasi,et al.  ConceptNet 3 : a Flexible , Multilingual Semantic Network for Common Sense Knowledge , 2007 .

[18]  Simone Paolo Ponzetto,et al.  Deriving a Large-Scale Taxonomy from Wikipedia , 2007, AAAI.

[19]  Preslav Nakov,et al.  SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals , 2009, SEW@NAACL-HLT.

[20]  Andrew McCallum,et al.  Structured Relation Discovery using Generative Models , 2011, EMNLP.

[21]  Estevam R. Hruschka,et al.  Discovering Relations between Noun Categories , 2011, EMNLP.

[22]  Enrique Alfonseca,et al.  Acquisition of instance attributes via labeled and related instances , 2010, SIGIR.

[23]  Anna Korhonen,et al.  Hierarchical Verb Clustering Using Graph Factorization , 2011, EMNLP.

[24]  Benjamin Van Durme,et al.  Weakly-Supervised Acquisition of Open-Domain Classes and Class Attributes from Web Documents and Query Logs , 2008, ACL.

[25]  Jens Lehmann,et al.  DBpedia: A Nucleus for a Web of Open Data , 2007, ISWC/ASWC.

[26]  L. Brown,et al.  Interval Estimation for a Binomial Proportion , 2001 .

[27]  Gerhard Weikum,et al.  SOFIE: a self-organizing framework for information extraction , 2009, WWW '09.

[28]  Zornitsa Kozareva,et al.  Learning Arguments and Supertypes of Semantic Relations Using Recursive Patterns , 2010, ACL.

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

[30]  Sunita Sarawagi,et al.  Annotating and searching web tables using entities, types and relationships , 2010, Proc. VLDB Endow..

[31]  Estevam R. Hruschka,et al.  Toward an Architecture for Never-Ending Language Learning , 2010, AAAI.

[32]  Patrick Pantel,et al.  VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations , 2004, EMNLP.

[33]  Praveen Paritosh,et al.  Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.

[34]  AgrawalRakesh,et al.  Mining association rules between sets of items in large databases , 1993 .

[35]  Jayant Madhavan,et al.  Recovering Semantics of Tables on the Web , 2011, Proc. VLDB Endow..

[36]  Patrick Pantel,et al.  DIRT @SBT@discovery of inference rules from text , 2001, KDD '01.

[37]  Patrick Pantel,et al.  The Omega Ontology , 2005, IJCNLP.

[38]  Jian Pei,et al.  Mining frequent patterns without candidate generation , 2000, SIGMOD 2000.

[39]  Benjamin Van Durme,et al.  What You Seek Is What You Get: Extraction of Class Attributes from Query Logs , 2007, IJCAI.

[40]  Gerhard Weikum,et al.  Scalable knowledge harvesting with high precision and high recall , 2011, WSDM '11.

[41]  Tom White,et al.  Hadoop: The Definitive Guide , 2009 .

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

[43]  Preslav Nakov,et al.  Solving Relational Similarity Problems Using the Web as a Corpus , 2008, ACL.

[44]  Simone Paolo Ponzetto,et al.  BabelNet: Building a Very Large Multilingual Semantic Network , 2010, ACL.

[45]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.