Datasets:
File size: 4,073 Bytes
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import csv
import datasets
import json
from io import StringIO
from pathlib import Path
import pandas as pd
_CITATION = """"""
_DESCRIPTION = """"""
_HOMEPAGE = ""
_URLS = {
"knowledge_questions": "data/knowledge_questions.json.zip",
"rc_questions": "data/rc_questions.json.zip",
"statutes": "data/statutes.tsv.zip",
}
_CONFIGS = {}
_CONFIGS["knowledge_questions"] = {
"description": "Answer knowledge questions about housing law in the different states.",
"features": {
"idx": datasets.Value("int32"),
"state": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"question_group": datasets.Value("int32"),
"statutes": datasets.Sequence(
{
"citation": datasets.Value("string"),
"excerpt": datasets.Value("string"),
}
),
"original_question": datasets.Value("string"),
"caveats": datasets.Sequence([datasets.Value("string")]),
},
"license": None,
}
_CONFIGS["rc_questions"] = {
"description": "Answer RC questions about housing law in the different states.",
"features": {
"idx": datasets.Value("int32"),
"state": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"question_group": datasets.Value("int32"),
"statutes": datasets.Sequence(
{
"statute_idx": datasets.Value("int32"),
"citation": datasets.Value("string"),
"excerpt": datasets.Value("string"),
}
),
"original_question": datasets.Value("string"),
"caveats": datasets.Sequence([datasets.Value("string")]),
},
"license": None,
}
_CONFIGS["statutes"] = {
"description": "Corpus of statutes",
"features": {
"citation": datasets.Value("string"),
"path": datasets.Value("string"),
"state": datasets.Value("string"),
"text": datasets.Value("string"),
"idx": datasets.Value("int32"),
},
"license": None,
}
class HousingQA(datasets.GeneratorBasedBuilder):
"""TODO"""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name=task, version=datasets.Version("1.0.0"), description=task,
)
for task in _CONFIGS
]
def _info(self):
features = _CONFIGS[self.config.name]["features"]
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(features),
homepage=_HOMEPAGE,
citation=_CITATION,
license=_CONFIGS[self.config.name]["license"],
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
downloaded_file_dir = Path(dl_manager.download_and_extract(_URLS[self.config.name]))
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"downloaded_file_dir": downloaded_file_dir,
"name": self.config.name,
},
),
]
def _generate_examples(self, downloaded_file_dir, name):
"""Yields examples as (key, example) tuples."""
if name in ["knowledge_questions"]:
fpath = downloaded_file_dir / f"{name}.json"
data = json.loads(fpath.read_text())
for id_line, data in enumerate(data):
yield id_line, data
if name in ["rc_questions"]:
fpath = downloaded_file_dir / f"{name}.json"
data = json.loads(fpath.read_text())
for id_line, data in enumerate(data):
yield id_line, data
if name in ["statutes"]:
fpath = downloaded_file_dir / f"{name}.tsv"
data = pd.read_csv(fpath, sep="\t", dtype={'index': 'int32'})
data = data.to_dict(orient="records")
for id_line, data in enumerate(data):
yield id_line, data |