Natural Language as the Basis for Meaning Representation and Inference
Identifieur interne : 001168 ( Main/Exploration ); précédent : 001167; suivant : 001169Natural Language as the Basis for Meaning Representation and Inference
Auteurs : Ido Dagan [Israël] ; Roy Bar-Haim [Israël] ; Idan Szpektor [Israël] ; Iddo Greental [Israël] ; Eyal Shnarch [Israël]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on logical representations for meaning, which may be viewed as being “external” to the natural language itself. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, which correspond closely to language structure. In many cases, such approaches lack a principled meaning representation and inference framework. We describe a generic semantic inference framework that operates directly on language-based structures, particularly syntactic trees. New trees are inferred by applying entailment rules, which provide a unified representation for varying types of inferences. Rules were generated by manual and automatic methods, covering generic linguistic structures as well as specific lexical-based inferences. Initial empirical evaluation in a Relation Extraction setting supports the validity and potential of our approach. Additionally, such inference is shown to improve the critical step of unsupervised learning of entailment rules, which in turn enhances the scope of the inference system. This paper corresponds to the invited talk of the first author at CICLING 2008.
Url:
DOI: 10.1007/978-3-540-78135-6_14
Affiliations:
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Classical approaches to semantic inference rely on logical representations for meaning, which may be viewed as being “external” to the natural language itself. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, which correspond closely to language structure. In many cases, such approaches lack a principled meaning representation and inference framework. We describe a generic semantic inference framework that operates directly on language-based structures, particularly syntactic trees. New trees are inferred by applying entailment rules, which provide a unified representation for varying types of inferences. Rules were generated by manual and automatic methods, covering generic linguistic structures as well as specific lexical-based inferences. Initial empirical evaluation in a Relation Extraction setting supports the validity and potential of our approach. Additionally, such inference is shown to improve the critical step of unsupervised learning of entailment rules, which in turn enhances the scope of the inference system. This paper corresponds to the invited talk of the first author at CICLING 2008.</div></front></TEI><affiliations><list><country><li>Israël</li></country></list><tree><country name="Israël"><noRegion><name sortKey="Dagan, Ido" sort="Dagan, Ido" uniqKey="Dagan I" first="Ido" last="Dagan">Ido Dagan</name></noRegion><name sortKey="Bar Haim, Roy" sort="Bar Haim, Roy" uniqKey="Bar Haim R" first="Roy" last="Bar-Haim">Roy Bar-Haim</name><name sortKey="Dagan, Ido" sort="Dagan, Ido" uniqKey="Dagan I" first="Ido" last="Dagan">Ido Dagan</name><name sortKey="Greental, Iddo" sort="Greental, Iddo" uniqKey="Greental I" first="Iddo" last="Greental">Iddo Greental</name><name sortKey="Shnarch, Eyal" sort="Shnarch, Eyal" uniqKey="Shnarch E" first="Eyal" last="Shnarch">Eyal Shnarch</name><name sortKey="Szpektor, Idan" sort="Szpektor, Idan" uniqKey="Szpektor I" first="Idan" last="Szpektor">Idan Szpektor</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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