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Browse files- README.md +35 -1
- epistolas.json +0 -0
- medieval_latin.py +82 -0
README.md
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---
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-
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---
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---
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language:
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- en
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tags:
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- medieval
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- latin
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- text-classification
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pretty_name: Abalone
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size_categories:
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- 100<n<1K
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task_categories: # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
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- text-classification
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---
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# Abalone
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The [Medieval Latin](https://openportal.isti.cnr.it/doc?id=people______::37b90c87470ef85c78e72b8a3c753293) authorship attribution dataset.
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Which Victorian author wrote the given text?
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Note: Only epistolas are included in this version of the dataset.
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# Configurations and tasks
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| **Configuration** | **Task** | Description |
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|-------------------|---------------------------|---------------------------------------------------------------|
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| authorship | Classification | Which Latin author wrote the given text?|
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# Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("mstz/medieval_latin", "authorship")["train"]
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```
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# Features
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|**Feature** |**Type** |
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|-------------------|---------------|
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| content | `[string]` |
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| epistola | `[string]` |
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| author | `[string]` |
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epistolas.json
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medieval_latin.py
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"""Medieval Latin."""
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from typing import List
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from functools import partial
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import datasets
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import pandas
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VERSION = datasets.Version("1.0.0")
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_ORIGINAL_FEATURE_NAMES = [
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"epistola",
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"author",
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"content"
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]
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_BASE_FEATURE_NAMES = [
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"epistola",
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"author",
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"content"
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]
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DESCRIPTION = "MedievalLatin dataset from the Gungor thesis.\"."
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_HOMEPAGE = "https://openportal.isti.cnr.it/doc?id=people______::37b90c87470ef85c78e72b8a3c753293"
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_URLS = ("https://openportal.isti.cnr.it/doc?id=people______::37b90c87470ef85c78e72b8a3c753293")
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_CITATION = """
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@techreport{oai:it.cnr:prodotti:438795,
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title = {MedLatin1 and MedLatin2: Two Datasets for the Computational Authorship Analysis of Medieval Latin Texts},
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author = {Corbara S. and Moreo A. and Sebastiani F. and Tavoni M.},
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institution = {Research report, 2020},
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year = {2020}
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}"""
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# Dataset info
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urls_per_split = {
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"train": "https://huggingface.co/datasets/mstz/medieval_latin/raw/main/epistolas.json",
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}
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features_types_per_config = {
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"authorship": {
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"epistola": datasets.Value("string"),
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"author": datasets.Value("string"),
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"content": datasets.Value("string")
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}
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}
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features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
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class MedievalLatinConfig(datasets.BuilderConfig):
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def __init__(self, **kwargs):
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super(MedievalLatinConfig, self).__init__(version=VERSION, **kwargs)
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self.features = features_per_config[kwargs["name"]]
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class MedievalLatin(datasets.GeneratorBasedBuilder):
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# dataset versions
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DEFAULT_CONFIG = "authorship"
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BUILDER_CONFIGS = [
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MedievalLatinConfig(name="authorship",
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description="authorship"),
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]
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def _info(self):
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info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
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features=features_per_config[self.config.name])
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return info
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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downloads = dl_manager.download_and_extract(urls_per_split)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]})
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]
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def _generate_examples(self, filepath: str):
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data = pandas.read_json(filepath)
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for row_id, row in data.iterrows():
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data_row = dict(row)
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yield row_id, data_row
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