la_core_web_lg_3.7.4

la_core_web_lg

• Person or organization developing model: Patrick J. Burns; with Nora Bernhardt [ner], Tim Geelhaar [tagger, morphologizer, parser, ner], Vincent Koch [ner]

• Model date: May 2023

• Model version: 3.7.4

• Model type: spaCy

• Information about training algorithms, parameters, fairness constraints or other applied approaches, and features: For information on the training workflow see p.4-5 of LatinCy: Synthetic Trained Pipelines for Latin NLP (https://arxiv.org/pdf/2305.04365v1)

• Paper or other resource for more information: Burns, P.J. 2023. "LatinCy: Synthetic Trained Pipelines for Latin NLP." arXiv:2305.04365 [cs.CL]. http://arxiv.org/abs/2305.04365.

• License: MIT

• Where to send questions or comments about the model: https://diyclassics.github.io/

Intended Use

• Primary intended uses: Morphological analysis, POS-Tagging, Lemmatizing, Parsing, NER

• Primary intended users: Classical Scholars

• Out-of-scope use cases: unknown

Data, Limitations, and Recommendations

• Data selection for training: Training data consists of latin UD-Treebanks, Wikipedia and OSCAR sentence data, the CC-100 Latin dataset and the Herodotos Project NER dataset

• Data selection for evaluation: Evaluation was done according to the spaCy workflow and is documented in the meta.json file found in the repository (https://huggingface.co/latincy/la_core_web_lg/blob/main/meta.json)

• Limitations: unknown