Paraphrase-Sense-Tagged Sentences

Clustering Sentences - Making Sense of Synonymous Sentences

ParaQuery: Making Sense of Paraphrase Collections

Pivoting on bilingual parallel corpora is a popular approach for paraphrase acquisition. Although such pivoted paraphrase collections have been successfully used to improve the performance of several different NLP applications, it is still difficult to get an intrinsic estimate of the quality and coverage of the paraphrases contained in these collections. We present ParaQuery, a tool that helps...

Bootstrapping Large Sense Tagged Corpora

The performance of Word Sense Disambiguation systems largely depends on the availability of sense tagged corpora. Since the semantic annotations are usually done by humans, the size of such corpora is limited to a handful of tagged texts. This paper proposes a generation algorithm that may be used to automatically create large sense tagged corpora. The approach is evaluated through comparative ...

Comparing Semantically Related Sentences: The Case of Paraphrase Versus Subsumption

Paraphrases and other semantically related sentences present a challenge to NLP and IR applications such as multi-document sum-marization and question answering systems. While it is generally agreed that paraphrases contain approximately equivalent ideas, they often diier from one another in subtle, yet non-trivial, ways. In this paper, we examine semantic diierences in cases of paraphrase and ...

Inducing Sense-Discriminating Context Patterns from Sense-Tagged Corpora

Traditionally, context features used in word sense disambiguation are based on collocation statistics and use only minimal syntactic and semantic information. Corpus Pattern Analysis is a technique for producing knowledge-rich context features that capture sense distinctions. It involves (1) identifying sense-carrying context patterns and (2) using the derived context features to discriminate b...