Non-NER tags are missing one letter
See original GitHub issueHow to reproduce the behaviour
If I execute the next code with POS tags
y_pred = [['ADJ', 'CONJ', 'VERB', 'AUX', 'NOUN', 'ADJ', 'SCONJ'], ['CONJ', 'SCONJ', 'X']]
y_true = [['ADJ', 'DET', 'VERB', 'AUX', 'NOUN', 'ADJ', 'SCONJ'], ['CONJ', 'ART', 'X']]
print(classification_report(y_true, y_pred))
What I get is:
precision recall f1-score support
CONJ 0.50 1.00 0.67 1
DJ 1.00 1.00 1.00 2
ERB 1.00 1.00 1.00 1
ET 0.00 0.00 0.00 1
ONJ 0.50 1.00 0.67 1
OUN 1.00 1.00 1.00 1
RT 0.00 0.00 0.00 1
UX 1.00 1.00 1.00 1
micro avg 0.78 0.78 0.78 9
macro avg 0.62 0.75 0.67 9
weighted avg 0.67 0.78 0.70 9
Here, all tags are missing the first letter. If I pass in suffix=True
, now the missing letter of the tags is the last one:
precision recall f1-score support
AD 1.00 1.00 1.00 2
AR 0.00 0.00 0.00 1
AU 1.00 1.00 1.00 1
CON 0.50 1.00 0.67 1
DE 0.00 0.00 0.00 1
NOU 1.00 1.00 1.00 1
SCON 0.50 1.00 0.67 1
VER 1.00 1.00 1.00 1
micro avg 0.78 0.78 0.78 9
macro avg 0.62 0.75 0.67 9
weighted avg 0.67 0.78 0.70 9
Moreover, one letter tags are ignored.
Your Environment
- Operating System:
Ubuntu 20.10
- Python Version:
Python 3.8.6
- Package Version:
seqeval==1.2.2
Issue Analytics
- State:
- Created 2 years ago
- Reactions:5
- Comments:7
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Option 2 would make most sense! I’ve been using option 1 as a workaround though 😃
Thanks for finding the key line, @liaeh! As I see it then, we only have two options:
B
.