Evaluation process: (1) you submit your results, (2) we perform the evaluation off-line and (3) return the final scores.

  • LivingNER-Species NER
$ cd src
$ python main.py -g ../gs-data/sample_entities_subtask1.tsv -p ../toy-data/sample_entities_subtask1_MISSING_ONE_FILE.tsv -s ner
According to file headers, you are on subtask ner
According to file headers, you are on subtask ner

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Clinical case name			Precision
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32032497_ES		nan
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Clinical case name			Recall
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32032497_ES		0.0
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Clinical case name			F-score
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32032497_ES		nan
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Micro-average metrics
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Micro-average precision = 1.0


Micro-average recall = 0.9568


Micro-average F-score = 0.9779

../toy-data/sample_entities_subtask1_MISSING_ONE_FILE.tsv|1.0|0.9568|0.9779
  • LivingNER-Species Norm
$ cd src
$ python main.py -g ../gs-data/sample_entities_subtask2.tsv -p ../toy-data/sample_entities_subtask2_predictions.tsv -s norm
According to file headers, you are on subtask norm, GS file
According to file headers, you are on subtask norm, predictions file
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/ann_parsing.py:46: UserWarning: There are duplicated entries in ../toy-data/sample_entities_subtask2_predictions.tsv. Keeping just the first one...
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/ann_parsing.py:59: UserWarning: Lines 1 in ../toy-data/sample_entities_subtask2_predictions.tsv contain unvalid codes. Valid codes are those that appear in ../ncbi_codes_unique.tsv. Ignoring lines with valid codes...

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Clinical case name			Precision
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32032497_ES		0.5
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Clinical case name			Recall
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32032497_ES		0.3333
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Clinical case name			F-score
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32032497_ES		0.4
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caso_clinico_medtropical54		1.0
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casos_clinicos_infecciosas1		1.0
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casos_clinicos_infecciosas141		1.0
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cc_onco908		1.0
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Micro-average metrics
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Micro-average precision = 0.9854


Micro-average recall = 0.9712


Micro-average F-score = 0.9783

../toy-data/sample_entities_subtask2_predictions.tsv|0.9854|0.9712|0.9783
  • LivingNER-Clinical IMPACT
$ cd src
$ python main.py -g ../gs-data/sample_subtask3.tsv -p ../toy-data/sample_subtask3_predictions.tsv -s app
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/ann_parsing.py:99: UserWarning: Lines 5 in ../toy-data/sample_subtask3_predictions.tsv contain unvalid codes. Valid codes are those that appear in ../ncbi_codes_unique.tsv. Ignoring lines with valid codes...
Basic metrics (not taking into account NCBI codes, just Y/N assignment)
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Pet
Precision = 1.0
Recall = 1.0
F1score = 1.0
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AnimalInjury
Precision = 1.0
Recall = 1.0
F1score = 1.0
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Food
Precision = 1.0
Recall = 1.0
F1score = 1.0
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Nosocomial
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/livingner_app.py:90: UserWarning: Precision score automatically set to zero because there are no predicted positives
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/livingner_app.py:104: UserWarning: Global F1 score automatically set to zero for simple metrics to avoid division by zero
/home/antonio/Documents/Work/BSC/Projects/micro/scripts/livingner-evaluation-library/src/livingner_app.py:110: UserWarning: Global F1 score automatically set to zero for complex metrics to avoid division by zero
Precision = 0
Recall = 0.0
F1score = 0
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Complex metrics (taking into account NCBI codes)
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Pet
Precision = 1.0
Recall = 1.0
F1score = 1.0
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AnimalInjury
Precision = 1.0
Recall = 1.0
F1score = 1.0
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Food
Precision = 1.0
Recall = 1.0
F1score = 1.0
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Nosocomial
Precision = 0
Recall = 0.0
F1score = 0
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