| """STAN small dataset by Bansal et al.."""
|
|
|
| import datasets
|
| import pandas as pd
|
| import ast
|
|
|
| _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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| }
|
| """
|
|
|
| _DESCRIPTION = """
|
| Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..
|
| """
|
| _URLS = {
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| "test": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/stan_small.csv"
|
| }
|
|
|
| class StanSmall(datasets.GeneratorBasedBuilder):
|
|
|
| VERSION = datasets.Version("1.0.0")
|
|
|
| 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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| supervised_keys=None,
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| homepage="https://github.com/mounicam/hashtag_master",
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| citation=_CITATION,
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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"] }),
|
| ]
|
|
|
| def _generate_examples(self, filepath):
|
|
|
| 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
|
| 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
|
| return output
|
|
|
| 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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|
|
| 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
|
| }
|
|
|
