IndexFziQ / IIE-NLP-Eyas-SemEval2021

Code of IIE-NLP-Eyas Team for ReCAM (Task 4) @SemEval2021 (https://arxiv.org/abs/2102.12777)

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SemEval2021 - Task 4: ReCAM: Reading Comprehension of Abstract Meaning @IIE-NLP-Eyas

ReCAM has three subtasks. Subtask 1 and 2 focus on evaluating machine learning models' performance with regard to two definitions of abstractness, which we call imperceptibility and nonspecificity, respectively. Subtask 3 aims to provide some insights to their relationships.

This repository contains preliminary code for the paper titled:

IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation. Yuqiang Xie, Luxi Xing, Wei Peng and Yue Hu*. SemEval 2021@ACL-IJCNLP2021.

Data

Data Format

Data is stored one-question-per-line in json format. Each instance of the data can be trated as a python dictinoary object. See examples below for further help in reading the data.

Sample

{
"article": "... observers have even named it after him, ``Abenomics". It is based on three key pillars -- the "three arrows" of monetary policy, fiscal stimulus and structural reforms in order to ensure long-term sustainable growth in the world's third-largest economy. In this weekend's upper house elections, ....",
"question": "Abenomics: The @placeholder and the risks",
"option_0": "chances",
"option_1": "prospective",
"option_2": "security",
"option_3": "objectives",
"option_4": "threats",
"label": 3
}
  • article : the article that provide the context for the question.
  • question : the question models are required to answer.
  • options : five answer options for the question. Model are required to select the true answer from 5 options.
  • label : index of the answer in options

Code

We implemented our System based on HuggingFace transformers. We are still cleaning up the code! Full code documentation will be ready soon!

Reference

Please cite our paper using the following bibtex:

@inproceedings{xie2021iienlpeyas,
   title={IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation},
   author={Yuqiang Xie and Luxi Xing and Wei Peng and Yue Hu},
   booktitle={Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)},
   year={2021},
}

About

Code of IIE-NLP-Eyas Team for ReCAM (Task 4) @SemEval2021 (https://arxiv.org/abs/2102.12777)

License:MIT License


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Language:Python 100.0%