Name
Abstract | ||
|---|---|---|
Paraphrases 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. |
Year | Venue | Keywords |
|---|---|---|
2014 | LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | paraphrasing,paraphrase fragments,semantic roles |
Field | DocType | Citations |
Computer science,Speech recognition,Paraphrase,Artificial intelligence,Natural language processing,Predicate (grammar),Syntax,Sentence,Semantic role labeling | Conference | 1 |
PageRank | References | Authors |
0.35 | 32 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michaela Regneri | 1 | 143 | 7.44 |
| Rui Wang | 2 | 20 | 2.47 |
| Manfred Pinkal | 3 | 1116 | 69.77 |