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README.md

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----
-annotations_creators:
-- machine-generated
-language_creators:
-- machine-generated
-language:
-- hi
-- en
-license:
-- unknown
-multilinguality:
-- multilingual
-size_categories:
-- unknown
-source_datasets:
-- original
-task_categories:
-- structure-prediction
-task_ids: []
-pretty_name: HashSet Distant
-tags:
-- word-segmentation
----
-
-# Dataset Card for HashSet Distant
-
-## Dataset Description
-
-- **Repository:** [prashantkodali/HashSet](https://github.com/prashantkodali/HashSet)
-- **Paper:** [HashSet -- A Dataset For Hashtag Segmentation](https://arxiv.org/abs/2201.06741)
-
-### Dataset Summary
-
-Hashset is a new dataset consisiting on 1.9k manually annotated and 3.3M loosely supervised tweets for testing the 
-efficiency of hashtag segmentation models. We compare State of The Art Hashtag Segmentation models on Hashset and other 
-baseline datasets (STAN and BOUN). We compare and analyse the results across the datasets to argue that HashSet can act 
-as a good benchmark for hashtag segmentation tasks.
-
-HashSet Distant: 3.3M loosely collected camel cased hashtags containing hashtag and their segmentation.
-
-### Languages
-
-Hindi and English.
-
-## Dataset Structure
-
-### Data Instances
-
-```
-{
-  'index': 282559, 
-  'hashtag': 'Youth4Nation', 
-  'segmentation': 'Youth 4 Nation'
-}
-```
-
-## Dataset Creation
-
-- All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: `hashtag` and `segmentation` or `identifier` and `segmentation`.
-
-- The only difference between `hashtag` and `segmentation` or between `identifier` and `segmentation` are the whitespace characters. Spell checking, expanding abbreviations or correcting characters to uppercase go into other fields.
-
-- There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as `_` , `:`, `~` ). 
-
-- If there are any annotations for named entity recognition and other token classification tasks, they are given in a `spans` field.
-
-## Additional Information
-
-### Citation Information
-
-```
-@article{kodali2022hashset,
-  title={HashSet--A Dataset For Hashtag Segmentation},
-  author={Kodali, Prashant and Bhatnagar, Akshala and Ahuja, Naman and Shrivastava, Manish and Kumaraguru, Ponnurangam},
-  journal={arXiv preprint arXiv:2201.06741},
-  year={2022}
-}
-```
-
-### Contributions
-
-This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github.com/ruanchaves/hashformers) library.

default/hashset_distant-test.parquet

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+oid sha256:bb465aabc7467e83eb4218abefc425f2638e548b24bd37cc95373b6da72c63e8
+size 13263420

hashset_distant.py

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-"""HashSet dataset."""
-
-import datasets
-import pandas as pd
-
-_CITATION = """
-@article{kodali2022hashset,
-  title={HashSet--A Dataset For Hashtag Segmentation},
-  author={Kodali, Prashant and Bhatnagar, Akshala and Ahuja, Naman and Shrivastava, Manish and Kumaraguru, Ponnurangam},
-  journal={arXiv preprint arXiv:2201.06741},
-  year={2022}
-}
-"""
-
-_DESCRIPTION = """
-Hashset is a new dataset consisiting on 1.9k manually annotated and 3.3M loosely supervised tweets for testing the 
-efficiency of hashtag segmentation models. We compare State of The Art Hashtag Segmentation models on Hashset and other 
-baseline datasets (STAN and BOUN). We compare and analyse the results across the datasets to argue that HashSet can act 
-as a good benchmark for hashtag segmentation tasks.
-
-HashSet Distant: 3.3M loosely collected camel cased hashtags containing hashtag and their segmentation.
-"""
-_URL = "https://raw.githubusercontent.com/prashantkodali/HashSet/master/datasets/hashset/HashSet-Distant.csv"
-
-class HashSetDistant(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "index": datasets.Value("int32"),
-                    "hashtag": datasets.Value("string"),
-                    "segmentation": datasets.Value("string")
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/prashantkodali/HashSet/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files }),
-        ]
-
-    def _generate_examples(self, filepath):
-        records = pd.read_csv(filepath).to_dict("records")
-        for idx, row in enumerate(records):
-            yield idx, {
-                "index": row["Unnamed: 0.1"],
-                "hashtag": row["Unsegmented_hashtag"],
-                "segmentation": row["Segmented_hashtag"]
-            }