Update README.md

README.md

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 license: cc0-1.0
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+task_categories:
+- question-answering
+language:
+- en
+size_categories:
+- 100M<n<1B
+---
+# COMPLEXTEMPQA Dataset
+
+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).
+
+## Dataset Description
+
+COMPLEXTEMPQA categorizes questions into three main types:
+- Attribute Questions
+- Comparison Questions
+- Counting Questions
+
+These categories are further divided based on their relation to events, entities, or time periods. 
+
+### Question Types and Counts
+
+| Question Type         | Subtype             | Count         |
+|-----------------------|---------------------|---------------|
+| Attribute             | Event               | 83,798        |
+| Attribute             | Entity              | 84,079        |
+| Attribute             | Time                | 9,454         |
+| Comparison            | Event               | 25,353,340    |
+| Comparison            | Entity              | 74,678,117    |
+| Comparison            | Time                | 54,022,952    |
+| Counting              | Event               | 18,325        |
+| Counting              | Entity              | 10,798        |
+| Counting              | Time                | 12,732        |
+| Multi-Hop             |                     | 76,933        |
+| Unnamed Event         |                     | 8,707,123     |
+| **Total**             |                     | **100,228,457**|
+
+### Metadata
+
+Each question in the dataset is accompanied by detailed metadata, including:
+- Type of question based on taxonomy
+- Wikidata IDs of the questioned entities or events
+- Country information for both questions and answers
+- Difficulty rating (easy or hard)
+- Time span related to the question
+
+## Dataset Characteristics
+
+### Size
+COMPLEXTEMPQA comprises over 100 million question-answer pairs, focusing on events, entities, and time periods from 1987 to 2023.
+
+### Complexity
+Questions require advanced reasoning skills, including multi-hop question answering, temporal aggregation, and across-time comparisons.
+
+### Taxonomy
+The dataset follows a unique taxonomy categorizing questions into attributes, comparisons, and counting types, ensuring comprehensive coverage of temporal queries.
+
+### Evaluation
+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.
+
+## Usage
+
+### Evaluation and Training
+COMPLEXTEMPQA can be used for:
+- Evaluating the temporal reasoning capabilities of large language models (LLMs)
+- Fine-tuning language models for better temporal understanding
+- Developing and testing retrieval-augmented generation (RAG) systems
+
+### Research Applications
+The dataset supports research in:
+- Temporal question answering
+- Information retrieval
+- Language understanding
+
+### Adaptation and Continual Learning
+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.
+
+## Access
+
+The dataset and code are freely available at [https://github.com/DataScienceUIBK/ComplexTempQA](https://github.com/DataScienceUIBK/ComplexTempQA).