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Learning First-Order Horn Clauses from Web Text
Stefan Schoenmackers
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Jesse Davis
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Oren Etzioni
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Daniel Weld
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Paper Details:
Month: October
Year: 2010
Location: Cambridge, MA
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Triple based Background Knowledge Ranking for Document Enrichment
Muyu Zhang
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Bing Qin
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Ting Liu
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Mao Zheng
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Relation Induction in Word Embeddings Revisited
Zied Bouraoui
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Shoaib Jameel
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Steven Schockaert
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Learning Verb Inference Rules from Linguistically-Motivated Evidence
Hila Weisman
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Jonathan Berant
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Idan Szpektor
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Ido Dagan
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Unsupervised Relation Extraction with General Domain Knowledge
Oier Lopez de Lacalle
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Mirella Lapata
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Unsupervised Induction of Cross-Lingual Semantic Relations
Mike Lewis
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Mark Steedman
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Two-Stage Method for Large-Scale Acquisition of Contradiction Pattern Pairs using Entailment
Julien Kloetzer
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Stijn De Saeger
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Kentaro Torisawa
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Chikara Hashimoto
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Jong-Hoon Oh
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Motoki Sano
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Kiyonori Ohtake
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NaturalLI: Natural Logic Inference for Common Sense Reasoning
Gabor Angeli
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Christopher D. Manning
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Mining Inference Formulas by Goal-Directed Random Walks
Zhuoyu Wei
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Jun Zhao
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Kang Liu
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Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
Rajarshi Das
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Arvind Neelakantan
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David Belanger
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Andrew McCallum
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Learning Entailment Relations by Global Graph Structure Optimization
Jonathan Berant
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Ido Dagan
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Jacob Goldberger
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Relation Extraction with Matrix Factorization and Universal Schemas
Sebastian Riedel
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Limin Yao
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Andrew McCallum
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Benjamin M. Marlin
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Injecting Logical Background Knowledge into Embeddings for Relation Extraction
Tim Rocktäschel
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Sameer Singh
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Sebastian Riedel
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Knowledge-Guided Linguistic Rewrites for Inference Rule Verification
Prachi Jain
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Mausam
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Stating the Obvious: Extracting Visual Common Sense Knowledge
Mark Yatskar
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Vicente Ordonez
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Ali Farhadi
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Global Learning of Typed Entailment Rules
Jonathan Berant
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Ido Dagan
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Jacob Goldberger
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Efficient Tree-based Approximation for Entailment Graph Learning
Jonathan Berant
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Ido Dagan
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Meni Adler
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Jacob Goldberger
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Learning to “Read Between the Lines” using Bayesian Logic Programs
Sindhu Raghavan
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Raymond Mooney
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Hyeonseo Ku
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Crowdsourcing Inference-Rule Evaluation
Naomi Zeichner
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Jonathan Berant
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Ido Dagan
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A Two Level Model for Context Sensitive Inference Rules
Oren Melamud
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Jonathan Berant
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Ido Dagan
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Jacob Goldberger
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Idan Szpektor
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Lexical Inference over Multi-Word Predicates: A Distributional Approach
Omri Abend
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Shay B. Cohen
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Mark Steedman
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Compositional Vector Space Models for Knowledge Base Completion
Arvind Neelakantan
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Benjamin Roth
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Andrew McCallum
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Combining Natural Logic and Shallow Reasoning for Question Answering
Gabor Angeli
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Neha Nayak
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Christopher D. Manning
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Combined Distributional and Logical Semantics
Mike Lewis
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Mark Steedman
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Johannes Welbl
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Pontus Stenetorp
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Sebastian Riedel
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Learning Typed Entailment Graphs with Global Soft Constraints
Mohammad Javad Hosseini
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Nathanael Chambers
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Siva Reddy
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Xavier R. Holt
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Shay B. Cohen
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Mark Johnson
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Mark Steedman
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Philosophers are Mortal: Inferring the Truth of Unseen Facts
Gabor Angeli
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Christopher Manning
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Incorporating Selectional Preferences in Multi-hop Relation Extraction
Rajarshi Das
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Arvind Neelakantan
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David Belanger
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Andrew McCallum
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A Consolidated Open Knowledge Representation for Multiple Texts
Rachel Wities
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Vered Shwartz
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Gabriel Stanovsky
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Meni Adler
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Ori Shapira
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Shyam Upadhyay
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Dan Roth
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Eugenio Martinez Camara
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Iryna Gurevych
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Ido Dagan
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Modeling Large-Scale Structured Relationships with Shared Memory for Knowledge Base Completion
Yelong Shen
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Po-Sen Huang
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Ming-Wei Chang
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Jianfeng Gao
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http://www.cs.washington.edu/research/sherlock-hornclauses/
Field Of Study
Task
Textual Entailment
Question Answering
Approach
Semi-supervised Learning
Language
English
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