Method and system for automatically extracting relations between concepts included in text
First Claim
1. A system for automatically extracting relations between concepts included in electronic text, comprising:
- 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;
wherein the semantic network further includes semantic information comprising at least one of;
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;
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
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; and
a linguistic engine for performing semantic disambiguation on the electronic text using the at least one 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 of the electronic text.
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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.
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Citations
55 Claims
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1. A system for automatically extracting relations between concepts included in electronic text, comprising:
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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;
wherein the semantic network further includes semantic information comprising at least one of;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;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 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; and a linguistic engine for performing semantic disambiguation on the electronic text using the at least one 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 of the electronic text. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A method for automatically extracting relations between concepts included in electronic text, comprising:
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accessing, by a program executing on a computer, a semantic network, wherein the semantic network comprises 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;
wherein the semantic network further includes semantic information comprising at least one of;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;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 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; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one 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 of the electronic text. - View Dependent Claims (29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54)
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55. An executable software product stored on a computer-readable medium containing program instructions for automatically extracting relations between concepts included in electronic text, the program instructions for:
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accessing, by a program executing on a computer, 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;
wherein the semantic network further includes semantic information comprising at least one of;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;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 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; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one 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 of the electronic text.
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Specification