Paper: A Phrase-Based Alignment Model for Natural Language Inference

ACL ID D08-1084
Title A Phrase-Based Alignment Model for Natural Language Inference
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

The alignment problem—establishing links between corresponding phrases in two related sentences—is as important in natural language inference (NLI) as it is in machine transla- tion (MT). But the tools and techniques of MT alignment do not readily transfer to NLI, where one cannot assume semantic equiva- lence, and for which large volumes of bitext are lacking. We present a new NLI aligner, the MANLI system, designed to address these challenges. It uses a phrase-based alignment representation, exploits external lexical re- sources, and capitalizes on a new set of su- pervised training data. We compare the per- formance of MANLI to existing NLI and MT aligners on an NLI alignment task over the well-known Recognizing Textual Entailment data. We show that MANLI significantly out- performs...