ABSA
Datasets
All datasets matching “ABSA”M-ABSA
M-ABSA
This repo contains the data for our paper M-ABSA: A Multilingual Dataset for Aspect-Based Sentiment Analysis.
Data Description:
This is a dataset suitable for the multilingual ABSA task with triplet extraction.
All datasets are stored in the data/ folder:
All dataset contains 7 domains.
domains = ["coursera", "hotel", "laptop", "restaurant", "phone", "sight", "food"]
Each dataset contains 21 languages.
langs = ["ar", "da", "de", "en", "es", "fr", "hi"… See the full description on the dataset page: https://huggingface.co/datasets/Multilingual-NLP/M-ABSA.FiQA_ABSAsetfit-absa-semeval-restaurants
Dataset Card for "tomaarsen/setfit-absa-semeval-restaurants"
Dataset Summary
This dataset contains the manually annotated restaurant reviews from SemEval-2014 Task 4, in the format as
understood by SetFit ABSA.
For more details, see https://aclanthology.org/S14-2004/
Data Instances
An example of "train" looks as follows.
{"text": "But the staff was so horrible to us.", "span": "staff", "label": "negative", "ordinal": 0}
{"text": "To be completely fair, the only… See the full description on the dataset page: https://huggingface.co/datasets/tomaarsen/setfit-absa-semeval-restaurants.semeval-absaThis dataset is built as a playground for aspect-based sentiment analysis.absa-quad
上述数据集为ABSA(Aspect-Based Sentiment Analysis)领域数据集，基本形式为从句子中抽取：方面术语、方面类别(术语类别)、术语在上下文中情感极性以及针对该术语的观点词，不同数据集抽取不同的信息，这点在jsonl文件的“instruction”键中有分别提到，在此我将其改造为了生成任务，需要模型按照一定格式生成抽取结果。
以acos数据集中抽取的jsonl文件一条数据举例：
{
"task_type": "generation",
"dataset": "acos",
"input": ["the computer has difficulty switching between tablet and computer ."],
"output": "[['computer', 'laptop usability', 'negative', 'difficulty']]",
"situation": "none",
"label": "",
"extra": ""… See the full description on the dataset page: https://huggingface.co/datasets/NEUDM/absa-quad.setfit-absa-semeval-laptops
Dataset Card for "tomaarsen/setfit-absa-semeval-laptops"
Dataset Summary
This dataset contains the manually annotated laptop reviews from SemEval-2014 Task 4, in the format as
understood by SetFit ABSA.
For more details, see https://aclanthology.org/S14-2004/
Data Instances
An example of "train" looks as follows.
{"text": "I charge it at night and skip taking the cord with me because of the good battery life.", "span": "cord", "label": "neutral", "ordinal": 0}… See the full description on the dataset page: https://huggingface.co/datasets/tomaarsen/setfit-absa-semeval-laptops.