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@@ -28,9 +28,9 @@ Ancient Chinese Language Understanding Evaluation (ACLUE) 是一个面向古代
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  The Ancient Chinese Language Understanding Evaluation (ACLUE) is an evaluation benchmark focused on ancient Chinese language comprehension. It aims to assess the performance of large-scale language models (LLMs) on understanding ancient Chinese.
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  ### 数据 (Data)
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- 该基准测试包含15个任务,涵盖了各个领域,包括词汇、句法、语义、推理和知识。我们为这15个任务提供了开发集和测试集数据,开发集中有5个问题,而测试集中则有100多个问题。我们鼓励研究人员使用ACLUE来测试和提升其模型在古代汉语语言理解方面的能力。ACLUE的任务来源于精心策划的公开资源和自动生成的古典汉语语料库的结合。这些问题涵盖了从夏朝(公元前2070年)到明朝(公元1368年)的广泛时间范围。ACLUE对所有任务都采用了多项选择题的形式。
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- The benchmark comprises 15 tasks spanning various domains, including lexical, syntactic, semantic, inference, and knowledge. We provide development and test dataset for each of 15 tasks, with 5 questions in development set and 100+ quesitons in test set. We encourage researchers to use ACLUE to test and enhance their models' abilities in ancient Chinese language understanding. ACLUE's tasks are derived from a combination of meticulously curated publicly available resources and automatically generated classical Chinese language corpora. The questions cover a wide temporal range from the Xia dynasty (2070 BCE) to the Ming dynasty (1368 CE). ACLUE employs a multiple-choice question format for all tasks.
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  ### 数据实例( Data Instances)
@@ -55,7 +55,7 @@ Each question in the dataset is a multiple-choice questions with 4 choices and o
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  D. 《虞美人》以其形式别致给人美感愉悦。
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  答案是:
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  ```
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- 以下提供了任务的类别、实例数量、问题平均长度以及任务的来源:
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  The category, number of instances, average length of the question, and origin of the tasks are provided below:
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@@ -80,9 +80,25 @@ The category, number of instances, average length of the question, and origin of
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  #### 加载数据 (Load data)
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  from datasets import load_dataset
 
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- dataset = load_dataset("tyouisen/aclue")
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  ```
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  The Ancient Chinese Language Understanding Evaluation (ACLUE) is an evaluation benchmark focused on ancient Chinese language comprehension. It aims to assess the performance of large-scale language models (LLMs) on understanding ancient Chinese.
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  ### 数据 (Data)
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+ 该基准测试包含15个任务,涵盖了各个领域,包括词汇、句法、语义、推理和知识。我们为这15个任务提供了开发集和测试集数据,开发集中有5个问题,而测试集中则有100多个问题。我们鼓励研究人员使用ACLUE来测试和提升其模型在古代汉语语言理解方面的能力。ACLUE的任务取自人工挑选的公开资源和自动生成的古代汉语语料库。这些问题涵盖了从夏朝(公元前2070年)到明朝(公元1368年)的广泛时间范围。ACLUE对所有任务都采用了多项选择题的形式。
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+ The benchmark comprises 15 tasks spanning various domains, including lexical, syntactic, semantic, inference, and knowledge. We provide development and test dataset for each of 15 tasks, with 5 questions in development set and 100+ quesitons in test set. We encourage researchers to use ACLUE to test and enhance their models' abilities in ancient Chinese language understanding. ACLUE's tasks are derived from a combination of manually curated questions from publicly available resources, and automatic generated questions from classical Chinese language corpora. The range of questions span from the Xia dynasty (2070 BCE) to the Ming dynasty (1368 CE). ACLUE employs a multiple-choice question format for all tasks.
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  ### 数据实例( Data Instances)
 
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  D. 《虞美人》以其形式别致给人美感愉悦。
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  答案是:
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  ```
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+ 以下列出了任务的类别、实例数量、问题平均长度以及任务的来源:
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  The category, number of instances, average length of the question, and origin of the tasks are provided below:
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  #### 加载数据 (Load data)
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  ```
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+ task_list = ['polysemy_resolution',
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+ 'poetry_sentiment_analysis',
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+ 'named_entity_recognition',
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+ 'basic_ancient_chinese',
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+ 'poetry_context_prediction',
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+ 'sentence_segmentation',
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+ 'couplet_prediction',
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+ 'poetry_appreciate',
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+ 'ancient_chinese_culture',
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+ 'ancient_phonetics',
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+ 'homographic_character_resolution',
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+ 'ancient_literature',
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+ 'ancient_medical',
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+ 'poetry_quality_assessment',
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+ 'reading_comprehension']
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+
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  from datasets import load_dataset
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+ dataset = {k: load_dataset(r"tyouisen/aclue", k) for k in task_list}
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  ```
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