| """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 HashSetDistantSampled(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"] | |
| } | |