#CrowdTruth: Biomedical Data Mining, Modeling & Semantic Integration (BDM2I 2015) @ISWC2015
CrowdTruth @DIR2015
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Transcript of CrowdTruth @DIR2015
• Annotator disagreement is signal, not noise.
• It is indicative of the variation in human semantic interpretation of signs
• It can indicate ambiguity, vagueness, similarity, over-generality, etc, as well as quality
http://CrowdTruth.org
• Goals:
○ collecting a relation extraction gold standard
○ improve the performance of a relation extraction classifier
http://CrowdTruth.org
TASK
→
1 1 1
1 1 1
1 1
1
1 1
1 1
1 1
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0 1 1 0 0 4 3 0 0 5 1 0
1
0 1 1 0 0 4 3 0 0 5 1 0
Unit vector for relation R6
Sentence Vector
Cosine = .55
• methodology • disagreement-aware
crowdsourcing to collect gold standard data
• metrics to capture disagreement
• software• online platform for
crowdsourcing task workflows and data analytics
• ground truth collection• medical relation extraction• salience in news and tweets• sound annotation
http://CrowdTruth.org