---
annotations_creators:
- expert-generated
language_creators:
- machine-generated
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
pretty_name: STAN Small
size_categories:
- unknown
source_datasets:
- original
task_categories:
- structure-prediction
task_ids:
- structure-prediction-other-word-segmentation
---

# Dataset Card for STAN Small

## Dataset Description

- **Repository:** [mounicam/hashtag_master](https://github.com/mounicam/hashtag_master)
- **Paper:** [Multi-task Pairwise Neural Ranking for Hashtag Segmentation](https://aclanthology.org/P19-1242/)

### Dataset Summary

The description below was taken from the paper "Multi-task Pairwise Neural Ranking for Hashtag Segmentation"
by Maddela et al..

"STAN large, our new expert curated dataset, which includes all 12,594 unique English hashtags and their 
associated tweets from the same Stanford dataset.

STAN small is the most commonly used dataset in previous work. However, after reexamination, we found annotation 
errors in 6.8% of the hashtags in this dataset, which is significant given that the error rate of the state-of-the art 
models is only around 10%. Most of the errors were related to named entities. For example, #lionhead, 
which refers to the “Lionhead” video game company, was labeled as “lion head”.

We therefore constructed the STAN large dataset of 12,594 hashtags with additional quality control for human annotations."

### Languages

English

## Dataset Structure

### Data Instances

```
{
    "index": 6,
    "hashtag": "justsayin",
    "segmentation": "just sayin",
    "alternatives": {
        "segmentation": [
            "just sayin",
            "just sayin "
        ]
    }
}
```

### Data Fields

- `index`: a numerical index.
- `hashtag`: the original hashtag.
- `segmentation`: the gold segmentation for the hashtag.
- `alternatives`: other segmentations that are also accepted as a gold segmentation.

### Citation Information

```
@misc{bansal2015deep,
      title={Towards Deep Semantic Analysis Of Hashtags}, 
      author={Piyush Bansal and Romil Bansal and Vasudeva Varma},
      year={2015},
      eprint={1501.03210},
      archivePrefix={arXiv},
      primaryClass={cs.IR}
}
```

### Contributions

This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github..com/ruanchaves/hashformers) library.