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Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
TLDR
We present HypeNET, an integrated path-based and distributional method for hypernymy detection, which achieves results comparable to distributional methods. Expand
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
TLDR
We create a new NLI test set that shows the deficiency of state-of-the-art models in inferences that require lexical and world knowledge, showing that these systems are limited in their generalization ability, failing to capture many simple inferences. Expand
Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection
TLDR
In this paper we perform an extensive evaluation of various unsupervised distributional measures for hypernymy detection, using several distributional semantic models that differ by context type and feature weighting. Expand
Path-based vs. Distributional Information in Recognizing Lexical Semantic Relations
TLDR
We follow the recent success of an integrated neural method for hypernymy detection (Shwartz et al., 2016) and extend it to recognize multiple relations. Expand
Unsupervised Commonsense Question Answering with Self-Talk
TLDR
We propose an unsupervised framework based on \emph{self-talk} as a novel alternative to multiple-choice commonsense tasks, and compete with models that obtain knowledge from external KBs. Expand
SemEval-2018 Task 9: Hypernym Discovery
TLDR
This paper describes the SemEval 2018 Shared Task on Hypernym Discovery. Expand
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution
Recognizing coreferring events and entities across multiple texts is crucial for many NLP applications. Despite the task's importance, research focus was given mostly to within-document entityExpand
Thinking Like a Skeptic: Defeasible Inference in Natural Language
TLDR
We introduce Defeasible NLI, a dataset for defeasible inference in natural language. Expand
Paraphrasing vs Coreferring: Two Sides of the Same Coin
TLDR
We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. Expand
Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition
TLDR
We create a unified framework that tests the capacity of representations to address lexical composition via classification tasks, focusing on detecting meaning shift. Expand
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