https://github.com/nicolay-r/semeval2024-task3
The supplementary sevice over THoR Chain-of-Thought framework as part of SemEval-2024 Task 3 paper
https://github.com/nicolay-r/semeval2024-task3
analysis datasets-preparation emotion-analysis semeval semeval-2024 span statistics
Last synced: 6 months ago
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The supplementary sevice over THoR Chain-of-Thought framework as part of SemEval-2024 Task 3 paper
- Host: GitHub
- URL: https://github.com/nicolay-r/semeval2024-task3
- Owner: nicolay-r
- License: mit
- Created: 2024-02-07T11:42:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-06T11:56:29.000Z (over 1 year ago)
- Last Synced: 2025-02-12T00:39:03.631Z (8 months ago)
- Topics: analysis, datasets-preparation, emotion-analysis, semeval, semeval-2024, span, statistics
- Language: Python
- Homepage: https://arxiv.org/abs/2404.03361
- Size: 39.1 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# SemEval-2024 Task 3: Codalab Service for [THOR-ECAC](https://github.com/nicolay-r/THOR-ECAC) • [](https://twitter.com/nicolayr_/status/1777005686611751415)
[](https://arxiv.org/abs/2404.03361)
[](https://nustm.github.io/SemEval-2024_ECAC/)
> **Update 05 March 2024**: The quick [arXiv paper](https://arxiv.org/abs/2404.03361) breakdowns 🔨 are @ [Twitter/X post](https://twitter.com/nicolayr_/status/1777005686611751415)
This repository shares data and submission-related code for training and handling results of
[THoR-ECAC framework](https://github.com/nicolay-r/THOR-ECAC), as a part of the SemEval-2024
paper **[nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thought on Emotion States](https://arxiv.org/abs/2404.03361)**
### [👉THoR-ECAC framework👈](https://github.com/nicolay-r/THOR-ECAC)
# Usage
1. Install necessary project dependencies as follows:
```bash
pip install -r dependencies.txt
```
2. Use [**download.py**](download.py) scripts for fetching ⬇️ all the task-related resources:
```bash
python download.py
```
3. Use the following shared scripts:
* **Resources Preparation for `pair-based` experiments in context**:
* [0_emotion_state.py](e3_pair_ft/0_emotion_state.py) -- script for pretraining data preparation, based on `states`;
* [0_emotion_cause.py](e3_pair_ft/0_emotion_cause.py) -- script for fine-tuning data preparation, based on `causes`;
* [1_ps_vocab.py](e3_pair_ft/1_ps_vocab.py) -- vocabulary preparation for manual spans corrections.
* **Spans correction algorithm**
[implementation](https://github.com/nicolay-r/SemEval2024-Task3/blob/b68d69da9b96f5ce6ab5b16521521d44ae1c504b/e3_pair_ft/utils_e.py#L56)
of the vocabulary-based spans-correction technique mentioned in paper.
* **Codalab submissions forming**:
* [2_submit](e3_pair_ft/2_submit.py) -- script for forming `*.json.zip` archive, compatible for submitting on Codalab platfom.
* Conversation data analysis:
* [task_statistics_json.py](task_statistics_json.py) -- `json` data analyzer;
* [task_statistics_submission.py](task_statistics_submission.py) -- `*json.zip` submissions analyzer.
# References
You can cite this work or [THoR-ECAC framework](https://github.com/nicolay-r/THOR-ECAC) as follows:
```bibtex
@article{rusnachenko2024nicolayr,
title={nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thought on Emotion States},
booktitle = "Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics",
author={Nicolay Rusnachenko and Huizhi Liang},
year= "2024",
month= jun,
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics"
}
```