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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Identifying character archetypes from movie scripts"""
from __future__ import absolute_import, division, print_function
import csv
import os
import datasets
_CITATION = """\
"""
_DESCRIPTION = """\
The character types identification dataset consists of movie
scripts annotated with character archetypes (Hero, Villain, Mentor, etc.).
"""
_URLS = {
"full_text": "https://drive.google.com/uc?export=download&id=1pivLkYl6l6_jJlQkHGsvziEn82GBapWc",
# "repo": "https://github.com/ghomasHudson/character-type-identification/archive/master.zip",
"repo": "https://github.com/ghomasHudson/character-type-identification/archive/refs/heads/master.zip"
}
class CharacterTypeID(datasets.GeneratorBasedBuilder):
"""Character Type Identification"""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
citation=_CITATION,
features=datasets.Features(
{
"document": {
"id": datasets.Value("string"),
"url": datasets.Value("string"),
"file_size": datasets.Value("int32"),
"word_count": datasets.Value("int32"),
"start": datasets.Value("string"),
"end": datasets.Value("string"),
"summary": {
"text": datasets.Value("string"),
"url": datasets.Value("string"),
"title": datasets.Value("string"),
},
"text": datasets.Value("string"),
},
"character_name": datasets.Value("string"),
"unit_quality_score": datasets.Value("float32"),
"character_type": datasets.ClassLabel(names=[
"Hero",
"Villain/Antagonist",
"Spouse/Partner/Lover of Hero",
"Spouse/Partner/Lover of Villain",
"Sidekick of Hero",
"Sidekick of Villain",
"Supporting role character of Hero",
"Supporting role character of Villain",
"Mentor",
"No Applicable Type"
])
}
),
homepage="https://github.com/ghomasHudson/character-type-identification",
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
dl_dir = dl_manager.download_and_extract(_URLS)
dl_dir["repo"] = os.path.join(dl_dir["repo"], "character-type-identification-master")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"repo_dir": dl_dir["repo"], "full_text_dir": dl_dir["full_text"], "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"repo_dir": dl_dir["repo"], "full_text_dir": dl_dir["full_text"], "split": "test"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"repo_dir": dl_dir["repo"], "full_text_dir": dl_dir["full_text"], "split": "valid"},
),
]
def _generate_examples(self, repo_dir, full_text_dir, split):
"""Yields examples."""
documents = {}
with open(os.path.join(repo_dir, "documents.csv"), encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
if row["set"] != split:
continue
documents[row["document_id"]] = row
summaries = {}
with open(os.path.join(repo_dir, "summaries.csv"), encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
if row["set"] != split:
continue
summaries[row["document_id"]] = row
char_fn = "character_labels.csv"
if split == "test":
char_fn = "character_labels_gold.csv"
with open(os.path.join(repo_dir, char_fn), encoding="utf-8") as f:
reader = csv.DictReader(f)
for id_, row in enumerate(reader):
if row["set"] != split:
continue
document_id = row["document_id"]
if document_id not in documents.keys():
print("NO KEY")
document = documents[document_id]
summary = summaries[document_id]
full_text = open(os.path.join(full_text_dir, document_id + ".txt"), encoding="latin-1").read()
res = {
"document": {
"id": document["document_id"],
"url": document["script_url"],
"file_size": document["script_file_size"],
"word_count": document["script_word_count"],
"start": document["script_start"],
"end": document["script_end"],
"summary": {
"text": summary["summary"],
"url": document["wiki_url"],
"title": document["wiki_title"],
},
"text": full_text,
},
"character_name": row["character_name"],
"unit_quality_score": row["unit_quality_score"],
"character_type": row["character_type"]
}
yield id_, res |