Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
License:
Fix `license` metadata
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README.md
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- machine-generated
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- en
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- unknown
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multilinguality:
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- monolingual
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pretty_name: Test-Stanford
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size_categories:
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- unknown
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source_datasets:
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- original
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task_categories:
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- structure-prediction
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task_ids:
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- structure-prediction-other-word-segmentation
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---
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# Dataset Card for Test-Stanford
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## Dataset Description
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- **Paper:** [Towards Deep Semantic Analysis Of Hashtags](https://arxiv.org/abs/1501.03210)
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### Dataset Summary
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Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..
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### Languages
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English
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## Dataset Structure
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### Data Instances
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```
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{
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"index": 1467856821,
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"hashtag": "therapyfail",
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"segmentation": "therapy fail",
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"gold_position": 8,
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"rank": {
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"position": [
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1,
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2,
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3,
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4,
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5,
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6,
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7,
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8,
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9,
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10,
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11,
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12,
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13,
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14,
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15,
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16,
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17,
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18,
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19,
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20
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],
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"candidate": [
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"therap y fail",
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"the rap y fail",
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"t her apy fail",
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"the rap yfail",
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"t he rap y fail",
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"thera py fail",
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"ther apy fail",
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"th era py fail",
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"therapy fail",
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"therapy fai l",
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"the r apy fail",
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"the rapyfa il",
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"the rapy fail",
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"t herapy fail",
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"the rapyfail",
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"therapy f ai l",
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"therapy fa il",
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"the rapyf a il",
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"therapy f ail",
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"the ra py fail"
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]
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}
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}
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```
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### Data Fields
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- `index`: a numerical index annotated by Kodali et al..
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- `hashtag`: the original hashtag.
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- `segmentation`: the gold segmentation for the hashtag.
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- `gold_position`: position of the gold segmentation on the `segmentation` field inside the `rank`.
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- `rank`: Rank of each candidate selected by a baseline word segmenter ( Segmentations Seeder Module ).
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## Dataset Creation
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- All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: `hashtag` and `segmentation` or `identifier` and `segmentation`.
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- 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.
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- There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as `_` , `:`, `~` ).
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- If there are any annotations for named entity recognition and other token classification tasks, they are given in a `spans` field.
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## Additional Information
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### Citation Information
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```
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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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### Contributions
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This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github.com/ruanchaves/hashformers) library.
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- machine-generated
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+
language:
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- en
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license:
|
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- unknown
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multilinguality:
|
| 11 |
+
- monolingual
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pretty_name: Test-Stanford
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size_categories:
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+
- unknown
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+
source_datasets:
|
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+
- original
|
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+
task_categories:
|
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+
- structure-prediction
|
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+
task_ids:
|
| 20 |
+
- structure-prediction-other-word-segmentation
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| 21 |
+
---
|
| 22 |
+
|
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# Dataset Card for Test-Stanford
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| 24 |
+
|
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+
## Dataset Description
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| 26 |
+
|
| 27 |
+
- **Paper:** [Towards Deep Semantic Analysis Of Hashtags](https://arxiv.org/abs/1501.03210)
|
| 28 |
+
|
| 29 |
+
### Dataset Summary
|
| 30 |
+
|
| 31 |
+
Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..
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| 32 |
+
|
| 33 |
+
### Languages
|
| 34 |
+
|
| 35 |
+
English
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| 36 |
+
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+
## Dataset Structure
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| 38 |
+
|
| 39 |
+
### Data Instances
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| 40 |
+
|
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+
```
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+
{
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"index": 1467856821,
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+
"hashtag": "therapyfail",
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+
"segmentation": "therapy fail",
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+
"gold_position": 8,
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+
"rank": {
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+
"position": [
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1,
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+
2,
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+
3,
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+
4,
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5,
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6,
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7,
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8,
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9,
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10,
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11,
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12,
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13,
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14,
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15,
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16,
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17,
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18,
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19,
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20
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],
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"candidate": [
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"therap y fail",
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"the rap y fail",
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+
"t her apy fail",
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+
"the rap yfail",
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+
"t he rap y fail",
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+
"thera py fail",
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+
"ther apy fail",
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+
"th era py fail",
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+
"therapy fail",
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+
"therapy fai l",
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+
"the r apy fail",
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+
"the rapyfa il",
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+
"the rapy fail",
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+
"t herapy fail",
|
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+
"the rapyfail",
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+
"therapy f ai l",
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+
"therapy fa il",
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+
"the rapyf a il",
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"therapy f ail",
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"the ra py fail"
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]
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+
}
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+
}
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+
```
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| 95 |
+
|
| 96 |
+
### Data Fields
|
| 97 |
+
|
| 98 |
+
- `index`: a numerical index annotated by Kodali et al..
|
| 99 |
+
- `hashtag`: the original hashtag.
|
| 100 |
+
- `segmentation`: the gold segmentation for the hashtag.
|
| 101 |
+
- `gold_position`: position of the gold segmentation on the `segmentation` field inside the `rank`.
|
| 102 |
+
- `rank`: Rank of each candidate selected by a baseline word segmenter ( Segmentations Seeder Module ).
|
| 103 |
+
|
| 104 |
+
## Dataset Creation
|
| 105 |
+
|
| 106 |
+
- All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: `hashtag` and `segmentation` or `identifier` and `segmentation`.
|
| 107 |
+
|
| 108 |
+
- 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.
|
| 109 |
+
|
| 110 |
+
- There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as `_` , `:`, `~` ).
|
| 111 |
+
|
| 112 |
+
- If there are any annotations for named entity recognition and other token classification tasks, they are given in a `spans` field.
|
| 113 |
+
|
| 114 |
+
## Additional Information
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
### Citation Information
|
| 118 |
+
|
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+
```
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+
@misc{bansal2015deep,
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+
title={Towards Deep Semantic Analysis Of Hashtags},
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| 122 |
+
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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+
### Contributions
|
| 131 |
+
|
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This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github.com/ruanchaves/hashformers) library.
|