Category Textual Entailment

Modeling Extractive Sentence Intersection via Subtree Entailment

Modeling Extractive Sentence Intersection via Subtree Entailment. Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, and Iryna Gurevych. COLING 2016. [pdf] Sentence intersection captures the semantic overlap of two texts, generalizing over paradigms such as textual entailment and semantic text similarity. Despite its modeling power, it has received little attention because it is difficult for […]

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Annotating Relation Inference in Context via Question Answering

Annotating Relation Inference in Context via Question Answering. Omer Levy and Ido Dagan. ACL 2016. [pdf] [supplementary] [slides] We convert the inference task to one of simple factoid question answering, allowing us to easily scale up to 16,000 high-quality examples. Code The code used to extract assertions and create the dataset is available here. Data […]

Learning to Exploit Structured Resources for Lexical Inference

Learning to Exploit Structured Resources for Lexical Inference. Vered Shwartz, Omer Levy, Ido Dagan and Jacob Goldberger. CoNLL 2015. [pdf] [supplementary] This paper presents a supervised framework for automatically selecting an optimized subset of resource relations for a given target inference task. Our approach enables the use of large-scale knowledge resources, thus providing a rich […]

A Simple Word Embedding Model for Lexical Substitution

A Simple Word Embedding Model for Lexical Substitution. Oren Melamud, Omer Levy, and Ido Dagan. VSM Workshop 2015. [pdf] We propose a simple model for lexical substitution, which is based on the popular skip-gram word embedding model. The novelty of our approach is in leveraging explicitly the context embeddings generated within the skip-gram model, which […]

Do Supervised Distributional Methods Really Learn Lexical Inference Relations?

Do Supervised Distributional Methods Really Learn Lexical Inference Relations? Omer Levy, Steffen Remus, Chris Biemann, and Ido Dagan. Short paper in NAACL 2015. [pdf] [slides] Distributional representations of words have been recently used in supervised settings for recognizing lexical inference relations between word pairs, such as hypernymy and entailment. We investigate a collection of these […]

Proposition Knowledge Graphs

Proposition Knowledge Graphs. Gabriel Stanovsky, Omer Levy, and Ido Dagan. AHA! Workshop 2014. [pdf] This position paper proposes a novel representation for Information Discovery — Proposition Knowledge Graphs. These extend the Open IE paradigm by representing semantic inter-proposition relations in a traversable graph. . . . . .

Focused Entailment Graphs for Open IE Propositions

Focused Entailment Graphs for Open IE Propositions. Omer Levy, Ido Dagan, and Jacob Goldberger. CoNLL 2014. [pdf] [slides] Open IE methods extract structured propositions from text. However, these propositions are neither consolidated nor generalized, and querying them may lead to insufficient or redundant information. This work suggests an approach to organize open IE propositions using […]

The Excitement Open Platform for Textual Inferences

The Excitement Open Platform for Textual Inferences. Bernardo Magnini, Roberto Zanoli, Ido Dagan, Kathrin Eichler, Günter Neumann, Tae-Gil Noh, Sebastian Padó, Asher Stern, and Omer Levy. Demo paper in ACL 2014. [pdf] This paper presents the Excitement Open Platform (EOP), a generic architecture and a comprehensive implementation for textual inference in multiple languages. Code The […]

Recognizing Partial Textual Entailment

Recognizing Partial Textual Entailment. Omer Levy, Torsten Zesch, Ido Dagan, and Iryna Gurevych. Short paper in ACL 2013. [pdf] [slides] Textual entailment is an asymmetric relation between two text fragments that describes whether one fragment can be inferred from the other. It thus cannot capture the notion that the target fragment is “almost entailed” by the […]

UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis

UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis. Torsten Zesch, Omer Levy, Iryna Gurevych, and Ido Dagan. SemEval 2013. [pdf] [slides] Given a question, a reference answer, and a student’s answer, the task is to determine whether the student answered correctly. While this is not a new task in itself, the challenge focuses on employing textual entailment technologies […]