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Table 1 Results over development set

From: Detecting modification of biomedical events using a deep parsing approach

Mod RMRS from Extra Gold UTurku
    R P F R P F
S PECULATION - W + 3 - 3 42.9 55.4 48.3 19.0 33.3 24.2
S PECULATION RASP - 16.7 66.7 26.7 5.5 26.1 9.0
S PECULATION ERG - 20.2 68.0 31.2 10.7 56.2 18.0
S PECULATION fb(ERG,RASP) - 25.0 61.8 35.6 13.1 50.0 20.8
S PECULATION cb(ERG,RASP) - 15.5 59.1 24.5 10.7 52.9 17.8
S PECULATION ERG W + 3 - 3 45.2 59.4 51.3 20.2 34.0 25.4
S PECULATION fb(ERG,RASP) W + 3 - 3 45.2 60.3 51.7 16.7 31.1 21.7
S PECULATION cb(ERG,RASP) W + 3 - 3 40.5 54.8 46.6 19.0 32.0 23.9
N EGATION - Negex 32.7 32.7 32.7 22.6 17.8 19.9
N EGATION - W + 3 - 4 51.8 54.8 53.3 25.4 33.7 29.0
N EGATION RASP - 12.7 35.9 18.8 5.4 26.1 9.0
N EGATION ERG - 26.4 72.5 38.7 15.4 34.0 21.2
N EGATION fb(ERG,RASP) - 35.4 66.1 46.1 17.3 34.6 23.0
N EGATION cb(ERG,RASP) - 29.1 64.0 40.0 13.6 34.1 19.5
N EGATION ERG W + 3 - 4 45.4 48.5 47.0 18.2 26.3 21.5
N EGATION fb(ERG,RASP) W + 3 - 4 44.6 66.2 53.3 19.1 33.3 24.3
N EGATION cb(ERG,RASP) W + 3 - 4 50.9 59.0 54.6 21.8 32.0 26.0
  1. Results over the development data using gold-standard Task 1 annotations and the UTurku Task 1 system ("fb" = fallback strategy, where we use the first source if possible, otherwise the second; "cb" = use undifferentiated RMRSs from each source to create feature vectors).