Datasets:
event2Mind

	"""TODO(event2Mind): Add a description here."""


	import csv
	import os

	import datasets


	# TODO(event2Mind): BibTeX citation
	_CITATION = """\
	@inproceedings{event2Mind,
	title={Event2Mind: Commonsense Inference on Events, Intents, and Reactions},
	author={Hannah Rashkin and Maarten Sap and Emily Allaway and Noah A. Smith† Yejin Choi},
	year={2018}
	}
	"""

	# TODO(event2Mind):\

	_DESCRIPTION = """\
	In Event2Mind, we explore the task of understanding stereotypical intents and reactions to events. Through crowdsourcing, we create a large corpus with 25,000 events and free-form descriptions of their intents and reactions, both of the event's subject and (potentially implied) other participants.
	"""
	_URL = "https://uwnlp.github.io/event2mind/data/event2mind.zip"


	class Event2mind(datasets.GeneratorBasedBuilder):
	"""TODO(event2Mind): Short description of my dataset."""

	# TODO(event2Mind): Set up version.
	VERSION = datasets.Version("0.1.0")

	def _info(self):
	# TODO(event2Mind): Specifies the datasets.DatasetInfo object
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# datasets.features.FeatureConnectors
	features=datasets.Features(
	{
	# These are the features of your dataset like images, labels ...
	"Source": datasets.Value("string"),
	"Event": datasets.Value("string"),
	"Xintent": datasets.Value("string"),
	"Xemotion": datasets.Value("string"),
	"Otheremotion": datasets.Value("string"),
	"Xsent": datasets.Value("string"),
	"Osent": datasets.Value("string"),
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage="https://uwnlp.github.io/event2mind/",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# TODO(event2Mind): Downloads the data and defines the splits
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	dl_dir = dl_manager.download_and_extract(_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(dl_dir, "train.csv")},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(dl_dir, "test.csv")},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(dl_dir, "dev.csv")},
	),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	# TODO(event2Mind): Yields (key, example) tuples from the dataset
	with open(filepath, encoding="utf-8") as f:
	data = csv.DictReader(f)
	for id_, row in enumerate(data):
	yield id_, {
	"Source": row["Source"],
	"Event": row["Event"],
	"Xintent": row["Xintent"],
	"Xemotion": row["Xemotion"],
	"Otheremotion": row["Otheremotion"],
	"Xsent": row["Xsent"],
	"Osent": row["Osent"],
	}