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"""Medieval Latin."""
from typing import List
from functools import partial
import datasets
import pandas
VERSION = datasets.Version("1.0.0")
_ORIGINAL_FEATURE_NAMES = [
"epistola",
"author",
"content"
]
_BASE_FEATURE_NAMES = [
"epistola",
"author",
"content"
]
DESCRIPTION = "MedievalLatin dataset from the Gungor thesis.\"."
_HOMEPAGE = "https://openportal.isti.cnr.it/doc?id=people______::37b90c87470ef85c78e72b8a3c753293"
_URLS = ("https://openportal.isti.cnr.it/doc?id=people______::37b90c87470ef85c78e72b8a3c753293")
_CITATION = """
@techreport{oai:it.cnr:prodotti:438795,
title = {MedLatin1 and MedLatin2: Two Datasets for the Computational Authorship Analysis of Medieval Latin Texts},
author = {Corbara S. and Moreo A. and Sebastiani F. and Tavoni M.},
institution = {Research report, 2020},
year = {2020}
}"""
# Dataset info
urls_per_split = {
"train": "https://huggingface.co/datasets/mstz/medieval_latin/raw/main/epistolas.json",
}
features_types_per_config = {
"authorship": {
"epistola": datasets.Value("string"),
"author": datasets.Value("string"),
"content": datasets.Value("string")
}
}
features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
class MedievalLatinConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(MedievalLatinConfig, self).__init__(version=VERSION, **kwargs)
self.features = features_per_config[kwargs["name"]]
class MedievalLatin(datasets.GeneratorBasedBuilder):
# dataset versions
DEFAULT_CONFIG = "authorship"
BUILDER_CONFIGS = [
MedievalLatinConfig(name="authorship",
description="authorship"),
]
def _info(self):
info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
features=features_per_config[self.config.name])
return info
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
downloads = dl_manager.download_and_extract(urls_per_split)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]})
]
def _generate_examples(self, filepath: str):
data = pandas.read_json(filepath)
for row_id, row in data.iterrows():
data_row = dict(row)
yield row_id, data_row
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