Benjamin Van Durme

TL;DR: The 1.0 release of the paraphrase database, PPDB, contains over 220 million paraphrase pairs, consisting of 73 million phrasal and 8 million lexical paraphrases, as well as 140million paraphrase patterns, which capture many meaning-preserving syntactic transformations.

TL;DR: It is shown that relatively modest information extraction techniques, when paired with a webscale corpus, can outperform these sophisticated approaches by roughly 34% relative gain.

TL;DR: This article proposed a hypothesis-only baseline for diagnosing NLI, which is able to significantly outperform a majority-class baseline across a number of NLI datasets, and showed that statistical irregularities may allow a model to perform NLI in some datasets beyond what should be achievable without access to the context.

TL;DR: The authors investigate word-level contextual representations from four recent models and investigate how they encode sentence structure across a range of syntactic, semantic, local, and long-range phenomena, finding that existing models trained on language modeling and translation produce strong representations for syntactic phenomena, but only offer comparably small improvements on semantic tasks over a non-contextual baseline.

TL;DR: This work has created layers of annotation on the English Gigaword v.5 corpus to render it useful as a standardized corpus for knowledge extraction and distributional semantics, and provides to the community a public reference set based on current state-of-the-art syntactic analysis and coreference resolution.