Data processing: speech signal processing – linguistics – language – Linguistics – Natural language
Reexamination Certificate
2011-03-01
2011-03-01
Albertalli, Brian L (Department: 2626)
Data processing: speech signal processing, linguistics, language
Linguistics
Natural language
C704S010000
Reexamination Certificate
active
07899666
ABSTRACT:
A method and system for automatically extracting relations between concepts included in electronic text is described. Aspects the exemplary embodiment include a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets. The semantic network further includes semantic information comprising at least one of: 1) an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; 2) a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and 3) a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language. A linguistic engine uses the semantic network to performing semantic disambiguation on the electronic text using one or more of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference.
REFERENCES:
patent: 5794050 (1998-08-01), Dahlgren et al.
patent: 6006221 (1999-12-01), Liddy et al.
patent: 2003/0130976 (2003-07-01), Au
patent: 2003/0217052 (2003-11-01), Rubenczyk
patent: 2003/0217335 (2003-11-01), Chung et al.
patent: 2004/0034652 (2004-02-01), Hofmann et al.
patent: 2005/0049852 (2005-03-01), Chao
patent: 2006/0074980 (2006-04-01), Sarkar
patent: 2007/0106493 (2007-05-01), Sanfilippo et al.
patent: 2007/0174041 (2007-07-01), Yeske
patent: 2007/0282598 (2007-12-01), Waelti et al.
patent: 2008/0201133 (2008-08-01), Cave et al.
patent: 2008/0215313 (2008-09-01), Waelti et al.
patent: WO2005003390 (2005-04-01), None
patent: WO2005033909 (2005-04-01), None
Edmonds et al., “Near-Synonymy and Lexical Choice”, Computational Linguistics, vol. 28, Issue 2, pp. 105-144, Jun. 2002.
Agirre et al., “Clustering WordNet Word Senses”, Proceedings of the Conference on Recent Advances on Natural Language, pp. 121-130, 2006.
Magnini et al., “Integrating Subject Field Codes into WordNet”, Proceedings of LREC-2000, Second International Conference on Language Resources and Evaluation, pp. 1413-1418, Jun. 2000.
Gangemi et al., “The OntoWordNet Project: extension and axiomatization of conceptual relations in WordNet”, Proc. of On the Move to Meaningful Internet Systems, pp. 820-838, 2003.
Oltramari et al., “Restructuring WordNet's Top-Level: The OntoClean approach”, Workshop Proceedings of OntoLex'2, Ontologies and Lexical Knowledge Bases, pp. 17-26, May 2002.
HTTP://XWN.HLT.UTDALLAS.EDU/WSD.HTML, “Semantic Annotation of WordNet Glosses”, Mar. 24, 2007, Published in: US.
Albertalli Brian L
Convergent Law Group LLP
Expert System S.p.A.
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