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Discovering Relations among Named Entities from Large Corpora
Takaaki Hasegawa
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Satoshi Sekine
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Ralph Grishman
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Paper Details:
Month: July
Year: 2004
Location: Barcelona, Spain
Venue:
ACL |
Citations
URL
Topic Identification for Fine-Grained Opinion Analysis
Veselin Stoyanov
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Claire Cardie
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A Linguistic Knowledge Discovery Tool: Very Large Ngram Database Search with Arbitrary Wildcards
Satoshi Sekine
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Recognizing Relation Expression between Named Entities based on Inherent and Context-dependent Features of Relational words
Toru Hirano
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Hisako Asano
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Yoshihiro Matsuo
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Genichiro Kikui
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Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters
Ang Sun
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Ralph Grishman
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Relation Classification via Convolutional Deep Neural Network
Daojian Zeng
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Kang Liu
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Siwei Lai
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Guangyou Zhou
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Jun Zhao
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Seeded Discovery of Base Relations in Large Corpora
Nicholas Andrews
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Naren Ramakrishnan
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Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
Longhua Qian
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Guodong Zhou
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Fang Kong
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Qiaoming Zhu
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Clustering-Based Stratified Seed Sampling for Semi-Supervised Relation Classification
Longhua Qian
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Guodong Zhou
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A generative model for unsupervised discovery of relations and argument classes from clinical texts
Bryan Rink
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Sanda Harabagiu
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Unsupervised Information Extraction with Distributional Prior Knowledge
Cane Wing-ki Leung
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Jing Jiang
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Kian Ming A. Chai
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Hai Leong Chieu
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Loo-Nin Teow
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Structured Relation Discovery using Generative Models
Limin Yao
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Aria Haghighi
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Sebastian Riedel
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Andrew McCallum
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Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Bonan Min
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Shuming Shi
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Ralph Grishman
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Chin-Yew Lin
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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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Queries as a Source of Lexicalized Commonsense Knowledge
Marius Paşca
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CORE: Context-Aware Open Relation Extraction with Factorization Machines
Fabio Petroni
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Luciano Del Corro
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Rainer Gemulla
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Learning to Recognize Discontiguous Entities
Aldrian Obaja Muis
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Wei Lu
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Investigating a Generic Paraphrase-Based Approach for Relation Extraction
Lorenza Romano
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Milen Kouylekov
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Idan Szpektor
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Ido Dagan
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Alberto Lavelli
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Outclassing Wikipedia in Open-Domain Information Extraction: Weakly-Supervised Acquisition of Attributes over Conceptual Hierarchies
Marius Paşca
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Discovering Relations Between Named Entities from a Large Raw Corpus Using Tree Similarity-Based Clustering
Min Zhang
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Jian Su
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Danmei Wang
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Guodong Zhou
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Chew Lim Tan
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Unsupervised Feature Selection for Relation Extraction
Jinxiu Chen
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Donghong Ji
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Chew Lim Tan
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Zhengyu Niu
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Automatic Paraphrase Discovery based on Context and Keywords between NE Pairs
Satoshi Sekine
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Named Entity Relation Mining using Wikipedia
Adrian Iftene
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Alexandra Balahur-Dobrescu
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Knowing the Author by the Company His Words Keep
Armin Hoenen
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Niko Schenk
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Preemptive Information Extraction using Unrestricted Relation Discovery
Yusuke Shinyama
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Satoshi Sekine
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Semi-supervised Relation Extraction with Label Propagation
Jinxiu Chen
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Donghong Ji
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Chew Lim Tan
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Zhengyu Niu
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A Systematic Exploration of the Feature Space for Relation Extraction
Jing Jiang
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ChengXiang Zhai
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Multi-Document Relationship Fusion via Constraints on Probabilistic Databases
Gideon Mann
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A Weighting Scheme for Open Information Extraction
Yuval Merhav
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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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Relation extraction pattern ranking using word similarity
Konstantinos Lambrou-Latreille
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Relation Extraction Using Label Propagation Based Semi-Supervised Learning
Jinxiu Chen
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Donghong Ji
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Chew Lim Tan
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Zhengyu Niu
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Names and Similarities on the Web: Fact Extraction in the Fast Lane
Marius Paşca
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Dekang Lin
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Jeffrey Bigham
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Andrei Lifchits
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Alpa Jain
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Unsupervised Relation Disambiguation Using Spectral Clustering
Jinxiu Chen
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Donghong Ji
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Chew Lim Tan
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Zhengyu Niu
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On-Demand Information Extraction
Satoshi Sekine
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HAL-Based Cascaded Model for Variable-Length Semantic Pattern Induction from Psychiatry Web Resources
Liang-Chih Yu
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Chung-Hsien Wu
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Fong-Lin Jang
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Fully Unsupervised Discovery of Concept-Specific Relationships by Web Mining
Dmitry Davidov
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Ari Rappoport
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Moshe Koppel
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Using Corpus Statistics on Entities to Improve Semi-supervised Relation Extraction from the Web
Benjamin Rosenfeld
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Ronen Feldman
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Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy Questions
Dmitry Davidov
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Ari Rappoport
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Unsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web
Yulan Yan
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Naoaki Okazaki
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Yutaka Matsuo
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Zhenglu Yang
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Mitsuru Ishizuka
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Unsupervised Relation Discovery with Sense Disambiguation
Limin Yao
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Sebastian Riedel
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Andrew McCallum
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Named Entity Disambiguation in Streaming Data
Alexandre Davis
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Adriano Veloso
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Altigran Soares
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Alberto Laender
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Wagner Meira Jr.
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Bilingual Active Learning for Relation Classification via Pseudo Parallel Corpora
Longhua Qian
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Haotian Hui
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Ya’nan Hu
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Guodong Zhou
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Qiaoming Zhu
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Generative Event Schema Induction with Entity Disambiguation
Kiem-Hieu Nguyen
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Xavier Tannier
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Olivier Ferret
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Romaric Besançon
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Exploiting Parallel News Streams for Unsupervised Event Extraction
Congle Zhang
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Stephen Soderland
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Daniel S. Weld
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TakeLab at SemEval-2018 Task 7: Combining Sparse and Dense Features for Relation Classification in Scientific Texts
Martin Gluhak
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Maria Pia di Buono
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Abbas Akkasi
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Jan Šnajder
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Comparison of Similarity Models for the Relation Discovery Task
Ben Hachey
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Boosting Unsupervised Relation Extraction by Using NER
Ronen Feldman
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Benjamin Rosenfeld
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Unsupervised Information Extraction Approach Using Graph Mutual Reinforcement
Hany Hassan
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Ahmed Hassan
|
Ossama Emam
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Unsupervised Relation Disambiguation with Order Identification Capabilities
Jinxiu Chen
|
Donghong Ji
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Chew Lim Tan
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Zhengyu Niu
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Cross-lingual Predicate Cluster Acquisition to Improve Bilingual Event Extraction by Inductive Learning
Heng Ji
|
Unsupervised techniques for discovering ontology elements from Wikipedia article links
Zareen Syed
|
Tim Finin
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A Combination of Topic Models with Max-margin Learning for Relation Detection
Dingcheng Li
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Swapna Somasundaran
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Amit Chakraborty
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Fast and Large-scale Unsupervised Relation Extraction
Sho Takase
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Naoaki Okazaki
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Kentaro Inui
|
http://www.nist.gov/speech/tests/ace/index.htm
http://nlp.cs.nyu.edu/oak/
Field Of Study
Task
Tagging
Information Extraction
Information Retrieval
Relation Extraction
Question Answering
Summarization
Language
English
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