Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
10K - 100K
License:
annotations_creators: | |
- expert-generated | |
language_creators: | |
- found | |
- expert-generated | |
language: | |
- en | |
license: | |
- cc-by-nc-4.0 | |
multilinguality: | |
- monolingual | |
paperswithcode_id: phrase-in-context | |
pretty_name: 'PiC: Phrase Similarity (PS)' | |
size_categories: | |
- 10K<n<100K | |
source_datasets: | |
- original | |
task_categories: | |
- text-classification | |
task_ids: | |
- semantic-similarity-classification | |
# Dataset Card for "PiC: Phrase Similarity" | |
## Table of Contents | |
- [Table of Contents](#table-of-contents) | |
- [Dataset Description](#dataset-description) | |
- [Dataset Summary](#dataset-summary) | |
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
- [Languages](#languages) | |
- [Dataset Structure](#dataset-structure) | |
- [Data Instances](#data-instances) | |
- [Data Fields](#data-fields) | |
- [Data Splits](#data-splits) | |
- [Dataset Creation](#dataset-creation) | |
- [Curation Rationale](#curation-rationale) | |
- [Source Data](#source-data) | |
- [Annotations](#annotations) | |
- [Personal and Sensitive Information](#personal-and-sensitive-information) | |
- [Considerations for Using the Data](#considerations-for-using-the-data) | |
- [Social Impact of Dataset](#social-impact-of-dataset) | |
- [Discussion of Biases](#discussion-of-biases) | |
- [Other Known Limitations](#other-known-limitations) | |
- [Additional Information](#additional-information) | |
- [Dataset Curators](#dataset-curators) | |
- [Licensing Information](#licensing-information) | |
- [Citation Information](#citation-information) | |
- [Contributions](#contributions) | |
## Dataset Description | |
- **Homepage:** [https://phrase-in-context.github.io/](https://phrase-in-context.github.io/) | |
- **Repository:** [https://github.com/phrase-in-context](https://github.com/phrase-in-context) | |
- **Paper:** | |
- **Leaderboard:** | |
- **Point of Contact:** [Thang Pham](<[email protected]>) | |
- **Size of downloaded dataset files:** 25.03 MB | |
- **Size of the generated dataset:** 16.22 MB | |
- **Total amount of disk used:** 41.25 MB | |
### Dataset Summary | |
PS is a binary classification task with the goal of predicting whether two multi-word noun phrases are semantically similar or not given *the same context* sentence. | |
This dataset contains ~56K pairs of two phrases along with their contexts used for disambiguation, since two phrases only sometimes are not enough for semantic comparison. | |
Around 28K positive examples were annotated by linguistic experts on <upwork.com> while the other 28K negative examples were created by randomly replacing 50% of the phrase tokens in the positive examples. | |
### Supported Tasks and Leaderboards | |
[More Information Needed] | |
### Languages | |
English. | |
## Dataset Structure | |
### Data Instances | |
**PS** | |
* Size of downloaded dataset files: 25.03 MB | |
* Size of the generated dataset: 16.22 MB | |
* Total amount of disk used: 41.25 MB | |
``` | |
{ | |
"phrase1": "greater presence", | |
"phrase2": "msie usage", | |
"sentence1": "The songs on the album feature a greater presence of band member Martin Swope's electronic and tape sound effects than with the band's previous recordings.", | |
"sentence2": "The songs on the album feature a msie usage of band member Martin Swope's electronic and tape sound effects than with the band's previous recordings.", | |
"label": 0, | |
"idx": 1, | |
} | |
``` | |
### Data Fields | |
The data fields are the same among all splits. | |
* phrase1: a string feature. | |
* phrase2: a string feature. | |
* sentence1: a string feature. | |
* sentence2: a string feature. | |
* label: a classification label, with negative (0) and positive (1). | |
* idx: an int32 feature. | |
### Data Splits | |
| name |train |validation|test | | |
|--------------------|----:|--------:|----:| | |
|PS |39436| 5634|11266| | |
## Dataset Creation | |
### Curation Rationale | |
[More Information Needed] | |
### Source Data | |
#### Initial Data Collection and Normalization | |
The source passages + answers are from Wikipedia and the source of queries were produced by our hired linguistic experts from [Upwork.com](https://upwork.com). | |
#### Who are the source language producers? | |
We hired 13 linguistic experts from [Upwork.com](https://upwork.com) for annotation and more than 1000 human annotators on Mechanical Turk along with another set of 5 Upwork experts for 2-round verification. | |
### Annotations | |
#### Annotation process | |
[More Information Needed] | |
#### Who are the annotators? | |
13 linguistic experts from [Upwork.com](https://upwork.com). | |
### Personal and Sensitive Information | |
No annotator identifying details are provided. | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
[More Information Needed] | |
### Discussion of Biases | |
[More Information Needed] | |
### Other Known Limitations | |
[More Information Needed] | |
## Additional Information | |
### Dataset Curators | |
This dataset is a joint work between Adobe Research and Auburn University. | |
Creators: [Thang M. Pham](https://scholar.google.com/citations?user=eNrX3mYAAAAJ), [David Seunghyun Yoon](https://david-yoon.github.io/), [Trung Bui](https://sites.google.com/site/trungbuistanford/), and [Anh Nguyen](https://anhnguyen.me). | |
[@PMThangXAI](https://twitter.com/pmthangxai) added this dataset to HuggingFace. | |
### Licensing Information | |
This dataset is distributed under [Creative Commons Attribution-NonCommercial 4.0 International (CC-BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/) | |
### Citation Information | |
``` | |
@article{pham2022PiC, | |
title={PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search}, | |
author={Pham, Thang and Yoon, David and Bui, Trung and Nguyen, Anh}, | |
journal={arXiv preprint}, | |
year={2022} | |
} | |
``` |