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
Model tree for daidalos-project/la_core_web_lg_3.7.4
Base model
latincy/la_core_web_lg