Datasets:
Languages:
Thai
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
expert-generated
Source Datasets:
original
Tags:
License:
File size: 4,100 Bytes
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Thai Literature Corpora (TLC): Corpora of machine-ingestible Thai classical literature texts."""
import json
import datasets
_CITATION = """\
@misc{
author={Sawatphol, Jitkapat},
title={Thai Literature Corpora},
year={2019},
howpublished={\\url{https://attapol.github.io/tlc.html}}
}
"""
_HOMEPAGE = "https://attapol.github.io/tlc.html"
_DESCRIPTION = """\
Thai Literature Corpora (TLC): Corpora of machine-ingestible Thai classical literature texts.
Release: 6/25/19
It consists of two datasets:
## TLC set
It is texts from [Vajirayana Digital Library](https://vajirayana.org/), stored by chapters and stanzas (non-tokenized).
tlc v.2.0 (6/17/19 : a total of 34 documents, 292,270 lines, 31,790,734 characters)
tlc v.1.0 (6/11/19 : a total of 25 documents, 113,981 lines, 28,775,761 characters)
## TNHC set
It is texts from Thai National Historical Corpus, stored by lines (manually tokenized).
tnhc v.1.0 (6/25/19 : a total of 47 documents, 756,478 lines, 13,361,142 characters)
"""
_URLs = {
"tlcv1.0": "https://github.com/jitkapat/thailitcorpus/releases/download/v.1.0/tlc_v.1.0.tar.gz",
"tlcv2.0": "https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz",
"tnhcv1.0": "https://github.com/jitkapat/thailitcorpus/releases/download/v.1.0/tnhc_v.1.0.tar.gz",
}
_FILENAMES = {
"tlcv1.0": "นิราศอิเหนา.json",
"tlcv2.0": "นิราศอิเหนา.json",
"tnhcv1.0": "กาพย์เห่เรือ.json",
}
class TlcConfig(datasets.BuilderConfig):
"""BuilderConfig for Tlc."""
def __init__(self, **kwargs):
"""BuilderConfig for Tlc.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(TlcConfig, self).__init__(**kwargs)
class Tlc(datasets.GeneratorBasedBuilder):
"""Thai Literature Corpora (TLC): Corpora of machine-ingestible Thai classical literature texts."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="tlcv1.0", version=datasets.Version("1.0.0"), description="Thai Literature Corpora"
),
datasets.BuilderConfig(
name="tlcv2.0", version=datasets.Version("2.0.0"), description="Thai Literature Corpora"
),
datasets.BuilderConfig(
name="tnhcv1.0",
version=datasets.Version("1.0.0"),
description="Thai Literature Corpora: Thai National Historical Corpus",
),
]
DEFAULT_CONFIG_NAME = "tlcv2.0"
def _info(self):
if self.config.name.startswith("tlc"):
features = datasets.Features(
{
"ch_num": datasets.Value("string"),
"title": datasets.Value("string"),
"text": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
}
)
else:
features = datasets.Features(
{
"text": datasets.Sequence((datasets.Value("string"))),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
archive = dl_manager.download(_URLs[self.config.name])
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"files": dl_manager.iter_archive(archive), "filepath": _FILENAMES[self.config.name]},
)
]
def _generate_examples(self, files, filepath):
_id = 0
for path, f in files:
if path == filepath:
data = json.loads(f.read().decode("utf-8"))
for d in data:
if self.config.name.startswith("tlc"):
yield _id, d
else:
yield _id, {"text": d}
_id += 1
break
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