UGARIT/flair_grc_multi_ner

Named Entity Recognition for Ancient Greek

Pretrained NER tagging model for ancient Greek

Scores & Tagset

Training

	Precision	Recall	F1-score	Support
PER	93.39%	96.33%	94.84%	2127
MISC	84.69%	92.50%	88.42%	933
LOC	89.55%	77.32%	82.99%	388

Evaluation

	Precision	Recall	F1-score	Support
PER	90.48%	91.94%	91.20%	124
MISC	89.29%	94.34%	91.74%	159
LOC	82.69%	65.15%	72.88%	66

Usage

from flair.data import Sentence
from flair.models import SequenceTagger
  
tagger = SequenceTagger.load("UGARIT/flair_grc_bert_ner")
sentence = Sentence('ταῦτα εἴπας ὁ Ἀλέξανδρος παρίζει Πέρσῃ ἀνδρὶ ἄνδρα Μακεδόνα ὡς γυναῖκα τῷ λόγῳ · οἳ δέ , ἐπείτε σφέων οἱ Πέρσαι ψαύειν ἐπειρῶντο , διεργάζοντο αὐτούς .')
tagger.predict(sentence)
for entity in sentence.get_spans('ner'):
    print(entity)

Citation

if you use this model, please consider citing this work:

@unpublished{yousefetal22
author = "Yousef, Tariq and Palladino, Chiara and Jänicke, Stefan",
title = "Transformer-Based Named Entity Recognition for Ancient Greek",
year = {2022},
month = {11},
doi = "10.13140/RG.2.2.34846.61761"
url = {https://www.researchgate.net/publication/365131651_Transformer-Based_Named_Entity_Recognition_for_Ancient_Greek}
}