Persian Universal Part-of-Speech Tagging in Flair
This is the universal part-of-speech tagging model for Persian that ships with Flair.
F1-Score: 97,73 (UD_PERSIAN)
Predicts Universal POS tags:
| tag | meaning |
|---|---|
| ADJ | adjective |
| ADP | adposition |
| ADV | adverb |
| AUX | auxiliary |
| CCONJ | coordinating conjunction |
| DET | determiner |
| INTJ | interjection |
| NOUN | noun |
| NUM | numeral |
| PART | particle |
| PRON | pronoun |
| PUNCT | punctuation |
| SCONJ | subordinating conjunction |
| VERB | verb |
| X | other |
Demo: How to use in Flair
Requires: Flair (pip install flair)
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("hamedkhaledi/persain-flair-upos")
# make example sentence
sentence = Sentence("مقامات مصری به خاطر حفظ ثبات کشور در منطقهای پرآشوب بر خود میبالند .")
tagger.predict(sentence)
#print result
print(sentence.to_tagged_string())
This yields the following output:
مقامات <NOUN> مصری <ADJ> به <ADP> خاطر <NOUN> حفظ <NOUN> ثبات <NOUN> کشور <NOUN> در <ADP> منطقهای <NOUN> پرآشوب <ADJ> بر <ADP> خود <PRON> میبالند <VERB> . <PUNCT>
Results
- F-score (micro) 0.9773
- F-score (macro) 0.9461
- Accuracy 0.9773
By class:
precision recall f1-score support
NOUN 0.9770 0.9849 0.9809 6420
ADP 0.9947 0.9916 0.9932 1909
ADJ 0.9342 0.9128 0.9234 1525
PUNCT 1.0000 1.0000 1.0000 1365
VERB 0.9840 0.9711 0.9775 1141
CCONJ 0.9912 0.9937 0.9925 794
AUX 0.9622 0.9799 0.9710 546
PRON 0.9751 0.9865 0.9808 517
SCONJ 0.9797 0.9757 0.9777 494
NUM 0.9948 1.0000 0.9974 385
ADV 0.9343 0.9033 0.9185 362
DET 0.9773 0.9711 0.9742 311
PART 0.9916 1.0000 0.9958 237
INTJ 0.8889 0.8000 0.8421 10
X 0.7143 0.6250 0.6667 8
micro avg 0.9773 0.9773 0.9773 16024
macro avg 0.9533 0.9397 0.9461 16024
weighted avg 0.9772 0.9773 0.9772 16024
samples avg 0.9773 0.9773 0.9773 16024
Loss: 0.12471389770507812
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