Aligning Predicate-Argument Structures for Paraphrase Fragment Extraction

16994

Authors

nan

Abstract

AbstractParaphrases and paraphrasing algorithms have been found of great importance in various natural language processing tasks. While most paraphrase extraction approaches extract equivalent sentences, sentences are an inconvenient unit for further processing, because they are too specific, and often not exact paraphrases. Paraphrase fragment extraction is a technique that post-processes sentential paraphrases and prunes them to more convenient phrase-level units. We present a new approach that uses semantic roles to extract paraphrase fragments from sentence pairs that share semantic content to varying degrees, including full paraphrases. In contrast to previous systems, the use of semantic parses allows for extracting paraphrases with high wording variance and different syntactic categories. The approach is tested on four different input corpora and compared to two previous systems for extracting paraphrase fragments. Our system finds three times as many good paraphrase fragments per sentence pair as the baselines, and at the same time outputs 30% fewer unrelated fragment pairs.

Keywords

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Full Content

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Labeled Text

AbstractParaphrases and paraphrasing algorithms have been found of great importance in various natural language processing tasks. While most paraphrase extraction approaches extract equivalent sentences, sentences are an inconvenient unit for further processing, because they are too specific, and often not exact paraphrases. Paraphrase fragment extraction is a technique that post-processes sentential paraphrases and prunes them to more convenient phrase-level units. We present a new approach that uses semantic roles to extract paraphrase fragments from sentence pairs that share semantic content to varying degrees, including full paraphrases. In contrast to previous systems, the use of semantic parses allows for extracting paraphrases with high wording variance and different syntactic categories. The approach is tested on four different input corpora and compared to two previous systems for extracting paraphrase fragments. Our system finds three times as many good paraphrase fragments per sentence pair as the baselines, and at the same time outputs 30% fewer unrelated fragment pairs.

Publication Details

Paper ID:
16994
Year:
2014
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan