| | """STAN small dataset by Bansal et al.."""
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| |
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| | import datasets
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| | import pandas as pd
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| | import ast
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| |
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| | _CITATION = """
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| | @misc{bansal2015deep,
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| | title={Towards Deep Semantic Analysis Of Hashtags},
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| | author={Piyush Bansal and Romil Bansal and Vasudeva Varma},
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| | year={2015},
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| | eprint={1501.03210},
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| | archivePrefix={arXiv},
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| | primaryClass={cs.IR}
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| | }
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| | """
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| |
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| | _DESCRIPTION = """
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| | Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..
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| | """
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| | _URLS = {
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| | "test": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/stan_small.csv"
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| | }
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| |
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| | class StanSmall(datasets.GeneratorBasedBuilder):
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| |
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| | VERSION = datasets.Version("1.0.0")
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| |
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| | def _info(self):
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| | return datasets.DatasetInfo(
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| | description=_DESCRIPTION,
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| | features=datasets.Features(
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| | {
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| | "index": datasets.Value("int32"),
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| | "hashtag": datasets.Value("string"),
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| | "segmentation": datasets.Value("string"),
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| | "alternatives": datasets.Sequence(
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| | {
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| | "segmentation": datasets.Value("string")
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| | }
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| | )
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| | }
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| | ),
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| | supervised_keys=None,
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| | homepage="https://github.com/mounicam/hashtag_master",
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| | citation=_CITATION,
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| | )
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| |
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| | def _split_generators(self, dl_manager):
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| | downloaded_files = dl_manager.download(_URLS)
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| | return [
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| | datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"] }),
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| | ]
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| |
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| | def _generate_examples(self, filepath):
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| |
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| | def get_segmentation(row):
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| | needle = row["hashtags"]
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| | haystack = row["goldtruths"][0].strip()
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| | output = ""
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| | iterator = iter(haystack)
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| | for char in needle:
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| | output += char
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| | while True:
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| | try:
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| | next_char = next(iterator)
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| | if next_char.lower() == char.lower():
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| | break
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| | elif next_char.isspace():
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| | output = output[0:-1] + next_char + output[-1]
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| | except StopIteration:
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| | break
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| | return output
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| |
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| | def get_alternatives(row, segmentation):
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| | alts = list(set([x.strip() for x in row["goldtruths"]]))
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| | alts = [x for x in alts if x != segmentation]
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| | alts = [{"segmentation": x} for x in alts]
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| | return alts
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| |
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| | records = pd.read_csv(filepath).to_dict("records")
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| | records = [{"hashtags": row["hashtags"], "goldtruths": ast.literal_eval(row["goldtruths"])} for row in records]
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| | for idx, row in enumerate(records):
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| | segmentation = get_segmentation(row)
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| | alternatives = get_alternatives(row, segmentation)
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| | yield idx, {
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| | "index": idx,
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| | "hashtag": row["hashtags"],
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| | "segmentation": segmentation,
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| | "alternatives": alternatives
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| | }
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| |
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