UGARIT/grc-ner-bert

Named Entity Recognition for Ancient Greek

Pretrained NER tagging model for ancient Greek

Data

We trained the models on available annotated corpora in Ancient Greek. There are only two sizeable annotated datasets in Ancient Greek, which are currently un- der release: the first one by Berti 2023, consists of a fully annotated text of Athenaeus’ Deipnosophists, developed in the context of the Digital Athenaeus project. The second one by Foka et al. 2020, is a fully annotated text of Pausanias’ Periegesis Hellados, developed in the context of the Digital Periegesis project. In addition, we used smaller corpora annotated by students and scholars on Recogito: the Odyssey annotated by Kemp 2021; a mixed corpus including excerpts from the Library attributed to Apollodorus and from Strabo’s Geography, annotated by Chiara Palladino; Book 1 of Xenophon’s Anabasis, created by Thomas Visser; and Demos- thenes’ Against Neaira, created by Rachel Milio.

Training Dataset

	Person	Location	NORP	MISC
Odyssey	2.469	698	0	0
Deipnosophists	14.921	2.699	5.110	3.060
Pausanias	10.205	8.670	4.972	0
Other Datasets	3.283	2.040	1.089	0
Total	30.878	14.107	11.171	3.060

---

Validation Dataset

	Person	Location	NORP	MISC
Xenophon	1.190	796	857	0

Results

Class	Metric	Test	Validation
LOC	precision	82.92%	87.10%
	recall	81.30%	87.10%
	f1	82.11%	87.10%
MISC	precision	80.43%	0
	recall	70.04%	0
	f1	74.87%	0
NORP	precision	87.10%	92.82%
	recall	90.81%	93.42%
	f1	88.92%	93.12%
PER	precision	92.61%	95.52%
	recall	92.94%	95.21%
	f1	92.77%	95.37%
Overall	precision	88.92%	92.63%
	recall	88.82%	92.79%
	f1	88.87%	92.71%
	Accuracy	97.28%	98.42%

Usage

This colab notebook contains the necessary code to use the model.

from transformers import pipeline

# create pipeline for NER
ner = pipeline('ner', model="UGARIT/grc-ner-bert", aggregation_strategy = 'first')
ner("ταῦτα εἴπας ὁ Ἀλέξανδρος παρίζει Πέρσῃ ἀνδρὶ ἄνδρα Μακεδόνα ὡς γυναῖκα τῷ λόγῳ · οἳ δέ , ἐπείτε σφέων οἱ Πέρσαι ψαύειν ἐπειρῶντο , διεργάζοντο αὐτούς .")

Output

[{'entity_group': 'PER',
  'score': 0.9999349,
  'word': 'αλεξανδρος',
  'start': 14,
  'end': 24},
 {'entity_group': 'NORP',
  'score': 0.9369563,
  'word': 'περση',
  'start': 33,
  'end': 38},
 {'entity_group': 'NORP',
  'score': 0.60742134,
  'word': 'μακεδονα',
  'start': 51,
  'end': 59},
 {'entity_group': 'NORP',
  'score': 0.9900457,
  'word': 'περσαι',
  'start': 105,
  'end': 111}]