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Table 6 Numbers of false positive PASMED’s relations according to the two annotators

From: Wide-coverage relation extraction from MEDLINE using deep syntax

 

C1

C2

Both

Total

Annotator A

257

120

66

443

Annotator B

311

50

17

378

Mean

284

85

41.5

410.5

 

69.18%

20.71%

10.11%

 
  1. We have classified them into three types of errors: C1–false positives caused by incorrect entity extraction (criterion 1), C2–false positives caused by not presented explicitly by linguistic expressions (criterion 2), and Both–false positives due to both C1 and C2.
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BMC Bioinformatics

ISSN: 1471-2105

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