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Selected Works

Yuliya Lierler

Syntactic Parsing and Knowledge Representation

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman Apr 2015

Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

Resolving attachment ambiguities is a pervasive problem in syntactic analysis. We propose and investigate an approach to resolving prepositional phrase attachment that centers around the ways of incorporating semantic knowledge derived from the lexico-semantic ontologies such as VERBNET and WORDNET.

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Aspccgtk: Towards Syntactic Parsing With Semantic Disambiguation, Yuliya Lierler, Peter Schueller Nov 2014

Aspccgtk: Towards Syntactic Parsing With Semantic Disambiguation, Yuliya Lierler, Peter Schueller

Yuliya Lierler

Natural language expressions are often ambiguous, allowing multiple interpretations. In this note we describe an approach that integrates syntactic analysis with semantic constraints in a system called ASPCCGTK. This system is based on Answer Set Programming — a popular declarative constraint programming paradigm.

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Towards A Tight Integration Of Syntactic Parsing With Semantic Disambiguation By Means Of Declarative Programming, Yuliya Lierler, Peter Schüller Nov 2013

Towards A Tight Integration Of Syntactic Parsing With Semantic Disambiguation By Means Of Declarative Programming, Yuliya Lierler, Peter Schüller

Yuliya Lierler

We propose and advocate the use of an advanced declarative programming paradigm – answer set programming – as a uniform platform for integrated approach towards syntax-semantic processing in natural language. We illustrate that (a) the parsing technology based on answer set programming implementation reaches performance sufficient for being a useful NLP tool, and (b) the proposed method for incorporating semantic information from FRAMENET into syntactic parsing may prove to be useful in allowing semantic-based disambiguation of syntactic structures.

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