GERBIL Experiment

Experiment URI:
Type: QA
Matching: Me - strong entity match
Annotator Dataset Language Micro F1 Micro Precision Micro Recall Macro F1 Macro Precision Macro Recall Error Count avg millis/doc Timestamp GERBIL version
HAWK feature (uploaded) QALD5 Train Hybrid en 0.1156 0.1136 0.1176 0.0577 0.0521 0.0792 0 0.025 2016-10-23 19:13:20 0.1.0
HAWK feature (uploaded) QALD5 Train Hybrid en Answer Type 0.7097 1 0.55 0.55 0.55 0.55 0 2016-10-23 19:13:20 0.1.0
HAWK feature (uploaded) QALD5 Train Hybrid en C2KB 0.0833 0.15 0.0577 0.2229 0.215 0.2521 0 2016-10-23 19:13:20 0.1.0
HAWK feature (uploaded) QALD5 Train Hybrid en P2KB 0.1071 0.1875 0.075 0.2286 0.2188 0.2625 0 2016-10-23 19:13:20 0.1.0
HAWK feature (uploaded) QALD5 Train Hybrid en RE2KB 0 0 0 0.2 0.2 0.2 0 2016-10-23 19:13:20 0.1.0
HAWK optimal (uploaded) QALD5 Train Hybrid en 0.5106 0.6429 0.4235 0.2929 0.2979 0.3063 0 0.05 2016-10-23 19:13:20 0.1.0
HAWK optimal (uploaded) QALD5 Train Hybrid en Answer Type 0.5455 1 0.375 0.375 0.375 0.375 0 2016-10-23 19:13:20 0.1.0
HAWK optimal (uploaded) QALD5 Train Hybrid en C2KB 0.1772 0.2593 0.1346 0.2729 0.2571 0.3292 0 2016-10-23 19:13:20 0.1.0
HAWK optimal (uploaded) QALD5 Train Hybrid en P2KB 0.2295 0.3333 0.175 0.2854 0.2663 0.345 0 2016-10-23 19:13:20 0.1.0
HAWK optimal (uploaded) QALD5 Train Hybrid en RE2KB 0.0164 0.0238 0.0125 0.2286 0.2278 0.23 0 2016-10-23 19:13:20 0.1.0