- Description:
Dolphin Math Word Problem dataset (2015), as presented in https://www.microsoft.com/en-us/research/uploads/prod/2016/02//dolphin-sigmadolphin.datasets.pdf
Homepage: https://www.microsoft.com/en-us/research/project/sigmadolphin-2/
Source code:
tfds.text.dolphin_number_word.DolphinNumberWordVersions:
0.0.1: Initial release.0.0.2: RaggedTensor fix. Equations and Sources represented as a singlestring with components delimited by spaces0.0.3(default): Reintroduced logic to handle edge-case involving examples without sources.
Download size:
280.42 KiBDataset size:
1.49 MiBAuto-cached (documentation): Yes
Splits:
| Split | Examples |
|---|---|
'test' |
3,507 |
'train' |
864 |
- Feature structure:
FeaturesDict({
'ans': Text(shape=(), dtype=string),
'equations': Text(shape=(), dtype=string),
'id': Text(shape=(), dtype=string),
'index': int32,
'sources': Text(shape=(), dtype=string),
'text': Text(shape=(), dtype=string),
})
- Feature documentation:
| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
| FeaturesDict | ||||
| ans | Text | string | ||
| equations | Text | string | ||
| id | Text | string | ||
| index | Tensor | int32 | ||
| sources | Text | string | ||
| text | Text | string |
Supervised keys (See
as_superviseddoc):('text', 'ans')Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@inproceedings{inproceedings,
author = {Shi, Shuming and Wang, Yuehui and Lin, Chin-Yew and Liu, Xiaojiang and Rui, Yong},
year = {2015},
month = {09},
pages = {},
title = {Automatically Solving Number Word Problems by Semantic Parsing and Reasoning},
doi = {10.18653/v1/D15-1135}
}