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Comparing Convolutional Neural Networks to Traditional Models for Slot Filling
Heike Adel
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Benjamin Roth
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Hinrich Schütze
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Paper Details:
Month: June
Year: 2016
Location: San Diego, California
Venue:
NAACL |
Citations
URL
Position-aware Attention and Supervised Data Improve Slot Filling
Yuhao Zhang
|
Victor Zhong
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Danqi Chen
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Gabor Angeli
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Christopher D. Manning
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Importance sampling for unbiased on-demand evaluation of knowledge base population
Arun Chaganty
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Ashwin Paranjape
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Percy Liang
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Christopher D. Manning
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Adversarial Training for Relation Extraction
Yi Wu
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David Bamman
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Stuart Russell
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Improving Slot Filling Performance with Attentive Neural Networks on Dependency Structures
Lifu Huang
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Avirup Sil
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Heng Ji
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Radu Florian
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Graph Convolution over Pruned Dependency Trees Improves Relation Extraction
Yuhao Zhang
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Peng Qi
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Christopher D. Manning
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DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction
Heike Adel
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Laura Ana Maria Bostan
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Sean Papay
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Sebastian Padó
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Roman Klinger
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Noise Mitigation for Neural Entity Typing and Relation Extraction
Yadollah Yaghoobzadeh
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Heike Adel
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Hinrich Schütze
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SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling
Matthias Hartung
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Hendrik ter Horst
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Frank Grimm
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Tim Diekmann
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Roman Klinger
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Philipp Cimiano
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LISA: Explaining Recurrent Neural Network Judgments via Layer-wIse Semantic Accumulation and Example to Pattern Transformation
Pankaj Gupta
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Hinrich Schütze
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Zero-shot Relation Classification as Textual Entailment
Abiola Obamuyide
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Andreas Vlachos
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FrameIt: Ontology Discovery for Noisy User-Generated Text
Dan Iter
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Alon Halevy
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Wang-Chiew Tan
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http://cistern.cis.lmu.de
http://lemurproject.org/clueweb12
http://cistern.cis.lmu.de
http://cistern.cis.lmu.de
Field Of Study
Linguistic Trends
Embeddings
Task
Tagging
Relation Extraction
Question Answering
Coreference Resolution
Machine Translation
Approach
Deep Learning
Language
English
Dataset
News
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