2012 SyntaxSemanticMappingforGeneral

• (Lian et al., 2012) ⇒ Ruiting Lian, Ben Goertzel, Shujing Ke, Jade O'Neill, Keyvan Sadeghi, Simon Shiu, Dingjie Wang, Oliver Watkins, and Gino Yu. (2012). “Syntax-Semantic Mapping for General Intelligence: Language Comprehension As Hypergraph Homomorphism, Language Generation As Constraint Satisfaction.” In: Proceedings of the 5th International Conference on Artificial General Intelligence. ISBN:978-3-642-35505-9 doi:10.1007/978-3-642-35506-6_17

Subject Headings: OpenCog System; RelEx System; NlGen System; Link Grammar; Relation Extraction System; AGI System.

Cited By

• Google Scholar: ~ 7 Citations (Retrieved:2019-10-17).
• ACM DL: ~ 1 Citations (Retrieved:2019-10-17).
• Semantic Scholar ~ 6 Citations (Retrieved:2019-10-17).

Quotes

Abstract

A new approach to translating between natural language expressions and hypergraph-based semantic knowledge representations is proposed. Language comprehension is formulated in terms of homomorphisms mapping syntactic parse trees into semantic hypergraphs, and language generation as constraint satisfaction based on constraints derived via applying the inverse relations of these homomorphisms. This provides an elegant approach to implementing semantically savvy NLP systems, and also to thinking about the feedbacks between syntactic and semantic processing that are the crux of generally intelligent NLP. A prototype of the approach created using the link parser and the OpenCog Atom semantic representation is described, and initial results presented. Routes to extending this prototype into something useful for aiding generally intelligent dialogue systems are discussed.

3 Link Parsing and RelEx

3.2 RelEx

RelEx is an English-language semantic relationship extractor, designed to postprocess the output of the link parser. It can identify subject, object, indirect object and many other dependency relationships between words in a sentence; it generates dependency trees, resembling those of dependency grammars. The output of the current version of RelEx on the example sentence given above is:

singular(cat)

singular(snake)

_subj(chase, cat)

_obj(chase, snake)

past(chase)

A list of the important RelEx relationship types is included in this paper’s online Supplementary Info.

 RelEx currently works via creating a tree with a FeatureNode corresponding to each word in the sentence, and then applying a series of rules to update the entries in this FeatureNode. The rules transform combinations of link parser links into RelEx dependency relations, sometimes acting indirectly via dynamics wherein one rule changes a feature in a word’s FeatureNode, and another rule then takes an action based on the changes the former rule made.

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References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 SyntaxSemanticMappingforGeneral	Ben Goertzel Ruiting Lian Shujing Ke Jade O'Neill Keyvan Sadeghi Simon Shiu Dingjie Wang Oliver Watkins Gino Yu			Syntax-Semantic Mapping for General Intelligence: Language Comprehension As Hypergraph Homomorphism, Language Generation As Constraint Satisfaction				10.1007/978-3-642-35506-6_17		2012