# web_questions

<br />

- **Description**:

This dataset consists of 6,642 question/answer pairs. The questions are supposed
to be answerable by Freebase, a large knowledge graph. The questions are mostly
centered around a single named entity. The questions are popular ones asked on
the web (at least in 2013).

- **Additional Documentation** :
  [Explore on Papers With Code](https://paperswithcode.com/dataset/webquestions)

- **Homepage** :
  <https://worksheets.codalab.org/worksheets/0xba659fe363cb46e7a505c5b6a774dc8a>

- **Source code** :
  [`tfds.question_answering.WebQuestions`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/question_answering/web_questions.py)

- **Versions**:

  - **`1.0.0`** (default): No release notes.
- **Download size** : `1.21 MiB`

- **Dataset size** : `983.88 KiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 2,032 |
| `'train'` | 3,778 |

- **Feature structure**:

    FeaturesDict({
        'answers': Sequence(Text(shape=(), dtype=string)),
        'question': Text(shape=(), dtype=string),
        'url': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
|   | FeaturesDict |   |   |   |
| answers | Sequence(Text) | (None,) | string |   |
| question | Text |   | string |   |
| url | Text |   | string |   |

- **Supervised keys** (See
  [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `None`

- **Figure**
  ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
  Not supported.

- **Examples**
  ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):

<button id="displaydataframe">Display examples...</button>

- **Citation**:

    @inproceedings{berant-etal-2013-semantic,
        title = "Semantic Parsing on {F}reebase from Question-Answer Pairs",
        author = "Berant, Jonathan  and
          Chou, Andrew  and
          Frostig, Roy  and
          Liang, Percy",
        booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
        month = oct,
        year = "2013",
        address = "Seattle, Washington, USA",
        publisher = "Association for Computational Linguistics",
        url = "https://www.aclweb.org/anthology/D13-1160",
        pages = "1533--1544",
    }