<--- Back to Details
First PageDocument Content
Logic / Logical consequence / Philosophy of logic / Textual entailment / SemEval / Entailment / Monotonicity of entailment / Implication / Implicature / Argument / WordNet / Machine learning
Date: 2016-08-02 12:42:41
Logic
Logical consequence
Philosophy of logic
Textual entailment
SemEval
Entailment
Monotonicity of entailment
Implication
Implicature
Argument
WordNet
Machine learning

Most babies are little and most problems are huge: Compositional Entailment in Adjective-Nouns Ellie Pavlick University of Pennsylvania

Add to Reading List

Source URL: www.cis.upenn.edu

Download Document from Source Website

File Size: 887,91 KB

Share Document on Facebook

Similar Documents

LNAIAn Approach for Textual Entailment Recognition Based on Stacking and Voting

LNAIAn Approach for Textual Entailment Recognition Based on Stacking and Voting

DocID: 1uSsV - View Document

Most babies are little and most problems are huge: Compositional Entailment in Adjective-Nouns Ellie Pavlick University of Pennsylvania

Most babies are little and most problems are huge: Compositional Entailment in Adjective-Nouns Ellie Pavlick University of Pennsylvania

DocID: 1rgDe - View Document

Dialog Natural Language Understanding using a Generic Textual Inference System Erel Segal-haLevi, Ido Dagan Department of Computer Science, Bar-Ilan University Ramat-Gan, Israel ,

Dialog Natural Language Understanding using a Generic Textual Inference System Erel Segal-haLevi, Ido Dagan Department of Computer Science, Bar-Ilan University Ramat-Gan, Israel ,

DocID: 1pVYk - View Document

Learning Natural Language Inference with LSTM Shuohang Wang School of Information Systems Singapore Management University

Learning Natural Language Inference with LSTM Shuohang Wang School of Information Systems Singapore Management University

DocID: 1pttv - View Document

Deep Learning and Structural Kernels for Semantic Inference: Question Answering Applications to Formal Text and Web Forums

Deep Learning and Structural Kernels for Semantic Inference: Question Answering Applications to Formal Text and Web Forums

DocID: 1mOpL - View Document