Abstract
We explore a new way to collect human annotated relations in text using Amazon Mechanical Turk. Given a knowledge base of relations and a corpus, we identify sentences which mention both an entity and an attribute that have some relation in the knowledge base. Each noisy sentence/relation pair is presented to multiple turkers, who are asked whether the sentence expresses the relation. We describe a design which encourages user efficiency and aids discovery of cheating. We also present results on inter-annotator agreement.
Original language | English (US) |
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Pages | 204-207 |
Number of pages | 4 |
State | Published - 2010 |
Externally published | Yes |
Event | 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Mturk 2010 at the 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2010 - Los Angeles, United States Duration: Jun 6 2010 → … |
Conference
Conference | 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Mturk 2010 at the 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2010 |
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Country/Territory | United States |
City | Los Angeles |
Period | 6/6/10 → … |
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language