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A Comparison of Knowledge Extraction Tools for the Semantic Web
Published on Jul 08, 20135209 Views
In the last years, basic NLP tasks: NER, WSD, relation extraction, etc. have been configured for Semantic Web tasks including ontology learning, linked data population, entity resolution, NL querying
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Chapter list
A Comparison of Knowledge Extraction Tools for the Semantic Web00:00
Objective and results01:01
Knowledge Extraction and the SW01:18
Trend against the “semiotic divide”03:42
Basic vs. application tasks05:01
Basic tasks in NLP and SW05:17
Sample translation table06:14
The assumptions06:35
What tools?07:20
Tools07:53
Disclaimer08:02
Summary of capabilities08:48
The test text09:16
Results09:44
Topic extraction10:17
Named entity recognition11:40
Named entity resolution12:22
Terminology extraction12:50
Word sense disambiguation14:10
Sense tagging (type induction)15:02
Relation extraction15:49
Event extraction17:57
SRL and frame detection18:59
Extraction from compositional lexicon19:57
Conclusions20:45
Thanks!22:50