Generalizing Sub-sentential Paraphrase Acquisition across Original Signal Type of Text Pairs

Aurélien Max, Houda Bouamor, Anne Vilnat

Abstract: This paper describes a study on the impact of the original signal (text, speech, visual scene, event) of a text pair on the task of both manual and automatic sub-sentential paraphrase acquisition. A corpus of 2,500 annotated sentences in English and French is described, and performance on this corpus is reported for an efficient system combination exploiting a large set of features for paraphrase recognition. A detailed quantified typology of sub-sentential paraphrases found in our corpus types is given.