README.md

metadata

annotations_creators:
  - machine-generated
language_creators:
  - machine-generated
language:
  - as
  - bn
  - gu
  - hi
  - kn
  - ml
  - mr
  - or
  - pa
  - ta
  - te
license:
  - cc0-1.0
multilinguality:
  - multilingual
pretty_name: IE-SemParse
size_categories:
  - 1M<n<10M
source_datasets:
  - original
task_categories:
  - text2text-generation
task_ids:
  - parsing

Dataset Card for "IE-SemParse"

Table of Contents

• Dataset Card for "IE-SemParse"
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset usage
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
      • Human Verification Process
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
    • Dataset Curators
    • Licensing Information
    • Citation Information

Dataset Description

• Homepage: https://github.com/divyanshuaggarwal/IE-SemParse
• Paper: Evaluating Inter-Bilingual Semantic Parsing for Indian Languages
• Point of Contact: Divyanshu Aggarwal

Dataset Summary

IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’), Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’), Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi (‘hi’), and Bengali (‘bn’).

Supported Tasks and Leaderboards

Tasks: Inter-Bilingual Semantic Parsing

Leaderboards: Currently there is no Leaderboard for this dataset.

Languages

• Assamese (as)
• Bengali (bn)
• Gujarati (gu)
• Kannada (kn)
• Hindi (hi)
• Malayalam (ml)
• Marathi (mr)
• Oriya (or)
• Punjabi (pa)
• Tamil (ta)
• Telugu (te)

...

Dataset usage

Code snippet for using the dataset using datasets library.

from datasets import load_dataset

dataset = load_dataset("Divyanshu/IE_SemParse")

Dataset Creation

Machine translation of 3 multilingual semantic Parsing datasets english dataset to 11 listed Indic Languages.

Curation Rationale

[More information needed]

Source Data

mTOP dataset

multilingualTOP dataset

multi-ATIS++ dataset

Initial Data Collection and Normalization

Detailed in the paper

Who are the source language producers?

Detailed in the paper

Human Verification Process

Detailed in the paper

Considerations for Using the Data

Social Impact of Dataset

Detailed in the paper

Discussion of Biases

Detailed in the paper

Other Known Limitations

Detailed in the paper

Dataset Curators

Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan

Licensing Information

Contents of this repository are restricted to only non-commercial research purposes under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). Copyright of the dataset contents belongs to the original copyright holders.

Citation Information

If you use any of the datasets, models or code modules, please cite the following paper:

@misc{aggarwal2023evaluating,
      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
      year={2023},
      eprint={2304.13005},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}