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Knowledge Base Construction with Epistemological Databases

Published on Jul 13, 20123721 Views

Andrew McCallum

AKBC-WEKEX 2012 - Montreal

Related categories

Information ExtractionNatural Language Processing Semantic WebText Mining

Chapter list

Knowledge Base Construction with Epistemological Databases00:00
Rexa00:32
Goal Application00:45
Attributes of our Task02:14
Knowledge Base Construction (1)03:05
Knowledge Base Construction (2)04:31
Knowledge Base Construction (3)06:51
“Epistemological Database” (1)08:16
“Epistemological Database” (2)09:39
“Epistemological Database” (3)10:29
“Epistemological Database” (4)11:07
“Epistemological Database” (5)11:51
“Epistemological Database” (6)12:00
“Epistemological Database” (7)12:13
“Epistemological Database” (8)12:15
“Epistemological Database” (9)12:18
Research Ingredients12:42
Entity Resolution (1)13:10
Entity Resolution (2)13:24
Entity Resolution (3)14:00
Entity Resolution (4)14:07
Entity Resolution (5)14:09
Entity Resolution (6)14:18
Entity Resolution (7)14:19
Entity Resolution (8)14:21
Entity Resolution in Parallel14:51
Parallelism = faster15:19
Distributed Entity Resolution15:39
Smart Parallelism = much faster17:03
Pair-based Coref (1)17:20
Pair-based Coref (2)17:28
Entity-based Coref (1)17:46
Entity-based Coref (2)18:19
Entity-based Coref (3)18:21
Hierarchical vs Pairwise Evaluation19:18
Entity-based Coref for Wikipedia & Newswire19:52
Currently: 100k Wikipedia entities, 20 years NYTimes20:02
Entity Resolution21:00
Probabilistic Reasoning about Human Edits21:32
Entity-based Coref (4)21:39
Entity-based Coref (5)22:33
Entity-based Coref (6)23:29
Benefits of Probabilistic Reasoning about Human Edits23:53
Robustness to Errorful Human Edits24:25
Benefits of Probabilistic Reasoning about Streaming Evidence24:47
Probabilistic Reasoning about Human Edits24:50
Relations with “Universal Schema” (1)25:16
Styles of Relation Extraction (1)25:27
Styles of Relation Extraction (2)26:02
Styles of Relation Extraction (3)27:23
Styles of Relation Extraction (4)28:09
Styles of Relation Extraction (5)29:01
Styles of Relation Extraction (6)29:56
Prob DB of “Universal Schema” (1)30:09
Prob DB of “Universal Schema” (2)31:39
Prob DB of “Universal Schema” (3)32:29
Prob DB of “Universal Schema” (4)33:14
Prob DB of “Universal Schema” (5)34:27
Prob DB of “Universal Schema” (6)34:42
Prob DB of “Universal Schema” (7)34:56
Prob DB of “Universal Schema” (8)35:53
Prob DB of “Universal Schema” (9)36:38
Prob DB of “Universal Schema” (10)37:30
Relations with “Universal Schema” (2)38:02
Prob-Programming, its Integration with Prob-DB38:12
Schema Matching38:23
Really Hairy Models (1)38:29
Really Hairy Models (2)38:37
Probabilistic Programming Languages38:41
Our Approach to Probabilistic Programming39:00
Prob-Programming & its Integratation with Prob-DB39:49
“Epistemological Database”39:52
Summary39:54
End43:24
Ingredients of our Approach43:31