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language: |
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- en |
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> 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。 |
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#### 以acos数据集中抽取的jsonl文件一条数据举例: |
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``` |
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{ |
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"task_type": "generation", |
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"dataset": "acos", |
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"input": ["the computer has difficulty switching between tablet and computer ."], |
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"output": "[['computer', 'laptop usability', 'negative', 'difficulty']]", |
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"situation": "none", |
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"label": "", |
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"extra": "", |
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"instruction": " |
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Task: Extracting aspect terms and their corresponding aspect categories, sentiment polarities, and opinion words. |
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Input: A sentence |
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Output: A list of 4-tuples, where each tuple contains the extracted aspect term, its aspect category, sentiment polarity, and opinion words (if any). Supplement: \"Null\" means that there is no occurrence in the sentence. |
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Example: |
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Sentence: \"Also it's not a true SSD drive in there but eMMC, which makes a difference.\" |
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Output: [['SSD drive', 'hard_disc operation_performance', 'negative', 'NULL']]' |
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" |
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} |
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``` |
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> 此处未设置label和extra,在instruction中以如上所示的字符串模板,并给出一个例子进行one-shot,ABSA领域数据集(absa-quad,acos,arts,aste-data-v2,mams,semeval-2014,semeval-2015,semeval-2016,towe)每个数据集对应instruction模板相同,内容有细微不同,且部分数据集存在同一数据集不同数据instruction内容不同的情况。 |
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#### 原始数据集 |
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- 数据[链接](https://github.com/NJUNLP/TOWE) |
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- Paper:[Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling](https://aclanthology.org/N19-1259/) |
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- 说明:原始数据由laptop14、restuarant14、restuarant15和restuarant16四个文件夹组成,四个文件夹的数据不同,但抽取的元素相同 |
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#### 当前SOTA |
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*数据来自[论文](https://aclanthology.org/N19-1259/)* |
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- 评价指标:F1-Score |
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- 模型:IOG |
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- laptop14:**71.35** |
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- restuarant14:**80.02** |
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- restuarant15:**73.25** |
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- restuarant16:**81.69** |
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- Paper:Paper:[Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling](https://aclanthology.org/N19-1259/) |
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- 说明:TOWE论文贡献为提出ABSA新的子任务(TOWE),并创建了新的数据集,但是据我在[google scholar](https://scholar.google.com/scholar?as_ylo=2023&hl=zh-CN&as_sdt=2005&sciodt=0,5&cites=10978596531168101977&scipsc=)的初步调研发现虽然后较多工作引用该论文,但是均未使用该TOWE数据集,因此暂且将提出TOWE数据集的论文模型作为SOTA模型 |
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