Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
extractive-qa
Languages:
code
Size:
100K - 1M
License:
annotations_creators: | |
- expert-generated | |
language: | |
- code | |
language_creators: | |
- found | |
license: | |
- mit | |
multilinguality: | |
- monolingual | |
pretty_name: codequeries | |
size_categories: | |
- 100K<n<1M | |
source_datasets: | |
- original | |
tags: | |
- code | |
- code question answering | |
- code semantic parsing | |
- codeqa | |
task_categories: | |
- question-answering | |
task_ids: | |
- extractive-qa | |
# Dataset Card for [Dataset Name] | |
## 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:** | |
- **Repository:** [Code repo](https://github.com/adityakanade/natural-cubert/) | |
- **Paper:** | |
### Dataset Summary | |
CodeQueries allows to explore extractive question-answering methodology over code | |
by providing semantic queries as question and answer pairs over code context involving | |
complex concepts and long chains of reasoning. | |
### Supported Tasks and Leaderboards | |
[More Information Needed] | |
### Languages | |
The code section have taken from `python` files. | |
## Dataset Structure | |
### Data Instances | |
All splits of all settings have same format. An example looks as follows - | |
``` | |
``` | |
### Data Fields | |
- examples | |
- query_name (query name to uniquely identify the query) | |
- context_blocks (code blocks supplied as input to the model for prediction) | |
- answer_spans (code in answer spans) | |
- supporting_fact_spans (code in supporting-fact spans) | |
- code_file_path (relative source file path w.r.t. ETH Py150 corpus) | |
- example_type (positive(1) or negative(0) example type) | |
- subtokenized_input_sequence (example subtokens) | |
- label_sequence (example subtoken labels) | |
### Data Splits | |
| |train |validation |test | | |
|--------------|:----:|:---------:|:---:| | |
|ideal | 9427 | 3270| 3245| | |
|prefix | - | - | 3245| | |
|sliding_window| - | - | 3245| | |
|file_ideal | - | - | 3245| | |
|twostep | - | - | 3245| | |
## Dataset Creation | |
### Curation Rationale | |
[More Information Needed] | |
### Source Data | |
#### Initial Data Collection and Normalization | |
[More Information Needed] | |
#### Who are the source language producers? | |
[More Information Needed] | |
### Annotations | |
#### Annotation process | |
[More Information Needed] | |
#### Who are the annotators? | |
[More Information Needed] | |
### Personal and Sensitive Information | |
[More Information Needed] | |
## 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 | |
[More Information Needed] | |
### Licensing Information | |
[More Information Needed] | |
### Citation Information | |
[More Information Needed] | |
### Contributions | |
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset. |