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---
language:
- en
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: Specter
tags:
- sentence-transformers
dataset_info:
- config_name: pair
features:
- name: anchor
dtype: string
- name: positive
dtype: string
splits:
- name: train
num_bytes: 55252049
num_examples: 380142
download_size: 24217449
dataset_size: 55252049
- config_name: triplet
features:
- name: anchor
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 152814049
num_examples: 684098
download_size: 62182004
dataset_size: 152814049
configs:
- config_name: pair
data_files:
- split: train
path: pair/train-*
- config_name: triplet
data_files:
- split: train
path: triplet/train-*
---
# Dataset Card for Specter
This dataset is a collection of title-related-unrelated triplets from Scientific Publications on Specter. See [Specter](https://github.com/allenai/specter) for additional information.
This dataset can be used directly with Sentence Transformers to train embedding models.
## Dataset Subsets
### `triplet` subset
* Columns: "anchor", "positive", "negative"
* Column types: `str`, `str`, `str`
* Examples:
```python
{
'anchor': "Integrating children's contributions in the interaction design process",
'positive': 'Designing for or designing with? Informant design for interactive learning environments',
'negative': 'Power Operation in ISD: Technological Frames Perspectives.',
}
```
* Collection strategy: Reading the Specter dataset from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), followed by deduplication.
* Deduplified: Yes
### `pair` subset
* Columns: "anchor", "positive"
* Column types: `str`, `str`
* Examples:
```python
{
'anchor': 'Time-dependent trajectory regression on road networks via multi-task learning',
'positive': 'Convex multi-task feature learning',
}
```
* Collection strategy: Reading the Specter dataset from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), only taking the title and related title, and then performing deduplication.
* Deduplified: Yes |