An Algorithm for Open Text Semantic Parsing

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Description

This paper describes an algorithm for open text shallow semantic parsing.

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9 p.

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Shi, Lei & Mihalcea, Rada, 1974- August 2004.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 494 times , with 12 in the last month . More information about this paper can be viewed below.

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UNT College of Engineering

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Description

This paper describes an algorithm for open text shallow semantic parsing.

Physical Description

9 p.

Notes

Abstract: This paper describes an algorithm for open text shallow semantic parsing. The algorithm relies on a frame dataset (FrameNet) and a semantic network (WordNet), to identify semantic relations between words in open text, as well as shallow semantic features associated with concepts in the text. Parsing semantic structures allows semantic units and constituents to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level.

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  • ROMAND Workshop on Robust Methods in Analysis of Natural Language Data, 2004, Geneva, Switzerland

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UNT Scholarly Works

The Scholarly Works Collection is home to materials from the University of North Texas community's research, creative, and scholarly activities and serves as UNT's Open Access Repository. It brings together articles, papers, artwork, music, research data, reports, presentations, and other scholarly and creative products representing the expertise in our university community. Access to some items in this collection may be restricted.

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Creation Date

  • August 2004

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

Description Last Updated

  • April 28, 2014, 1:40 p.m.

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Shi, Lei & Mihalcea, Rada, 1974-. An Algorithm for Open Text Semantic Parsing, paper, August 2004; (digital.library.unt.edu/ark:/67531/metadc30953/: accessed April 28, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.