Abstract
PATTY is a system for automatically distilling relational patterns from the Web, for example, the pattern "X covered Y" between a singer and someone else's song. We have extracted a large collection of such patterns and organized them in a taxonomic manner, similar in style to the WordNet thesaurus but capturing relations (binary predicates) instead of concepts and classes (unary predicates). The patterns are organized by semantic types and synonyms, and they form a hierarchy based on subsumptions. For example, "X covered Y" is subsumed by "X sang Y", which in turn is subsumed by "X performed Y" (where X can be any musician, not just a singer). In this paper we give an overview of the PATTY system and the resulting collections of relational patterns. We discuss the four main components of PATTY's architecture and a variety of use cases, including the paraphrasing of relations, and semantic search over subjectpredicate- object triples. This kind of search can handle entities, relations, semantic types, noun phrases, and relational phrases.
- S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, Z.G. Ives: DBpedia: A Nucleus for a Web of Open Data, ISWC/ASWC, pp. 722--735 2007 Google ScholarDigital Library
- K. D. Bollacker, C. Evans, P. Paritosh, T. Sturge, J. Taylor: Freebase: a Collaboratively Created Graph Database for Structuring Human Knowledge. SIGMOD, pp. 1247--1250, 2008 Google ScholarDigital Library
- A. Carlson, J. Betteridge, R.C. Wang, E.R. Hruschka, T.M. Mitchell: Coupled Semi-supervised Learning for Information Extraction, WSDM, pp. 101--110, 2010 Google ScholarDigital Library
- A. Fader, S. Soderland, O. Etzioni: Identifying Relations for Open Information Extraction, EMNLP, pp. 1535--1545, 2011 Google ScholarDigital Library
- L. Fang, A. Das Sarma, C. Yu, P. Bohannon: REX: Explaining Relationships between Entity Pairs. PVLDB 5(3), pp. 241--252, 2011 Google ScholarDigital Library
- G. Limaye, S. Sarawagi, S. Chakrabarti: Annotating and Searching Web Tables Using Entities, Types and Relationships. PVLDB 3(1), pp. 1338--1347, 2010 Google ScholarDigital Library
- M.-C. de Marneffe, B. MacCartney and C. D. Manning. Generating Typed Dependency Parses from Phrase Structure Parses. LREC, 2006Google Scholar
- T. Mohamed, E.R. Hruschka, T.M. Mitchell: Discovering Relations between Noun Categories, EMNLP, pp. 1447--1455, 2011 Google ScholarDigital Library
- N. Nakashole, T. Tylenda, G. Weikum: Fine-grained Semantic Typing of Emerging Entities, ACL, to appear 2013.Google Scholar
- N. Nakashole, G. Weikum, F. Suchanek: PATTY: A Taxonomy of Relational Patterns with Semantic Types, EMNLP, pp.1135--1145. 2012 Google ScholarDigital Library
- N. Nakashole, G. Weikum, F. Suchanek: Discovering and Exploring Relations on the Web. PVLDB 5(10), pp. 1982--1985, 2012 Google ScholarDigital Library
- N. Nakashole: Automatic Extraction of Facts, Relations, and Entities for Web-Scale Knowledge Base Population. PhD Thesis, Saarland University, 2012Google Scholar
- F.M. Suchanek, G. Kasneci, G. Weikum: Yago: a Core of Semantic Knowledge, WWW, pp. 697--706, 2007 Google ScholarDigital Library
- P. Venetis, A. Halevy, J. Madhavan, M. Pasca, W. Shen, F. Wu, G. Miao, C. Wu: Recovering Semantics of Tables on the Web, VLDB, pp. 528--538, 2011 Google ScholarDigital Library
- W. Wu, H. Li, H. Wang, K. Zhu: Probase: A Probabilistic Taxonomy for Text Understanding, SIGMOD, pp. 481--492, 2012 Google ScholarDigital Library
- M. Yahya, K.Berberich, S. Elbassuoni, M. Ramanath, V. Tresp, W. Weikum: Natural Language Questions for the Web of Data. EMNLP, pp. 379--390, 2012 Google ScholarDigital Library
- L. Yao, A. Haghighi, S. Riedel, A. McCallum: Structured Relation Discovery using Generative Models. EMNLP, pp. 1456--1466, 2011 Google ScholarDigital Library
Index Terms
Discovering semantic relations from the web and organizing them with PATTY
Recommendations
PATTY: a taxonomy of relational patterns with semantic types
EMNLP-CoNLL '12: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language LearningThis 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 ...
Semantic web reasoners and languages
Semantic web reasoners and languages enable the semantic web to function. Some of the latest reasoning models developed in the last few years are: DLP, FaCT, RACER, Pellet, MSPASS, CEL, Cerebra Engine, QuOnto, KAON2, HermiT and others. Some software ...
Discovering semantic relations using prepositional phrases
ISMIS'12: Proceedings of the 20th international conference on Foundations of Intelligent SystemsExtracting semantical relations between concepts from texts is an important research issue in text mining and ontology construction. This paper presents a machine learning-based approach to semantic relation discovery using prepositional phrases. The ...
Comments