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--- |
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license: cc0-1.0 |
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task_categories: |
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- question-answering |
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language: |
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- en |
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size_categories: |
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- 100M<n<1B |
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--- |
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# ComplexTempQA Dataset |
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ComplexTempQA is a large-scale dataset designed for complex temporal question answering (TQA). It consists of over 100 million question-answer pairs, making it one of the most extensive datasets available for TQA. The dataset is generated using data from Wikipedia and Wikidata and spans questions over a period of 36 years (1987-2023). |
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**Note:** We have a smaller version consisting of questions from the time period 1987 until 2007. |
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## Dataset Description |
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ComplexTempQA categorizes questions into three main types: |
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- Attribute Questions |
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- Comparison Questions |
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- Counting Questions |
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These categories are further divided based on their relation to events, entities, or time periods. |
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### Question Types and Counts |
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| | Question Type | Subtype | Count | |
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|--|-----------------------|---------------------|---------------| |
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|1a| Attribute | Event | 83,798 | |
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|1b| Attribute | Entity | 84,079 | |
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|1c| Attribute | Time | 9,454 | |
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|2a| Comparison | Event | 25,353,340 | |
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|2b| Comparison | Entity | 74,678,117 | |
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|2c| Comparison | Time | 54,022,952 | |
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|3a| Counting | Event | 18,325 | |
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|3b| Counting | Entity | 10,798 | |
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|3c| Counting | Time | 12,732 | |
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| | Multi-Hop | | 76,933 | |
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| | Unnamed Event | | 8,707,123 | |
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| | **Total** | | **100,228,457**| |
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### Metadata |
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- **id**: A unique identifier for each question. |
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- **question**: The text of the question being asked. |
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- **answer**: The answer(s) to the question. |
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- **type**: The type of question based on the dataset’s taxonomy. |
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- **rating**: A numerical rating indicating the difficulty of the question (`0` for easy, `1` for hard). |
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- **timeframe**: The start and end dates relevant to the question. |
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- **question_entity**: List of Wikidata IDs related to the entities in the question. |
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- **answer_entity**: List of Wikidata IDs related to the entities in the answer. |
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- **question_country**: List of Wikidata IDs of the countries associated with the questioned entities or events. |
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- **answer_country**: List of Wikidata IDs of the countries associated with the answered entities or events. |
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- **is_unnamed**: A flag indicating if the question contains an implicitly described event (`1` for yes, `0` for no). |
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## Dataset Characteristics |
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### Size |
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ComplexTempQA comprises over 100 million question-answer pairs, focusing on events, entities, and time periods from 1987 to 2023. |
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### Complexity |
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Questions require advanced reasoning skills, including multi-hop question answering, temporal aggregation, and across-time comparisons. |
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### Taxonomy |
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The dataset follows a unique taxonomy categorizing questions into attributes, comparisons, and counting types, ensuring comprehensive coverage of temporal queries. |
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### Evaluation |
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The dataset has been evaluated for readability, ease of answering before and after web searches, and overall clarity. Human raters have assessed a sample of questions to ensure high quality. |
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## Usage |
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### Evaluation and Training |
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ComplexTempQA can be used for: |
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- Evaluating the temporal reasoning capabilities of large language models (LLMs) |
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- Fine-tuning language models for better temporal understanding |
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- Developing and testing retrieval-augmented generation (RAG) systems |
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### Research Applications |
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The dataset supports research in: |
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- Temporal question answering |
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- Information retrieval |
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- Language understanding |
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### Adaptation and Continual Learning |
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ComplexTempQA's temporal metadata facilitates the development of online adaptation and continual training approaches for LLMs, aiding in the exploration of time-based learning and evaluation. |
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## Access |
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The dataset and code are freely available at [https://github.com/DataScienceUIBK/ComplexTempQA](https://github.com/DataScienceUIBK/ComplexTempQA). |
