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---
language:
- en
size_categories:
- 1M<n<10M
task_categories:
- feature-extraction
- text-classification
- sentence-similarity
dataset_info:
features:
- name: sentence
dtype: string
- name: cluster
dtype: int64
splits:
- name: train
num_bytes: 59231273
num_examples: 990526
download_size: 22602562
dataset_size: 59231273
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "WikiAnswers Small"
## Dataset Summary
`nikhilchigali/wikianswers_small` is a subset of the `embedding-data/WikiAnswers` dataset ([Link](https://huggingface.co/datasets/embedding-data/WikiAnswers)).
As opposed to the original dataset with `3,386,256` rows, this dataset contains only 4% of the total rows(sets). The sets of sentences have been unraveled into individual items with corresponding cluster IDs to identify sentences from the same set.
## Languages
English.
## Dataset Structure
Each example in the dataset contains a sentence and its cluster id of other equivalent sentences. The sentences in the same cluster are paraphrases of each other.
```
{"sentence": [sentence], "cluster": [cluster_id]}
{"sentence": [sentence], "cluster": [cluster_id]}
{"sentence": [sentence], "cluster": [cluster_id]}
...
{"sentence": [sentence], "cluster": [cluster_id]}
```
### Usage Example
Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
```python
from datasets import load_dataset
dataset = load_dataset("nikhilchigali/wikianswers_small")
```
The dataset is loaded as a `DatasetDict` and has the format for `N` examples:
```python
DatasetDict({
train: Dataset({
features: ['sentence', "cluster"],
num_rows: N
})
})
```
Review an example `i` with:
```python
dataset["train"][i]
```
### Source Data
* `embedding-data/WikiAnswers` on HuggingFace ([Link](https://huggingface.co/datasets/embedding-data/WikiAnswers))
#### Note: This dataset is for the owner's personal use and claims no rights whatsoever. |