CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
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Abstract (arXiv)
Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very rare. In this paper, we focus on automatic Chinese taxonomy construction and propose an effective generation and verification framework to build a large-scale and high-quality Chinese taxonomy. In the generation module, we extract isA relations from multiple sources of Chinese encyclopedia, which ensures the coverage. To further improve the precision of taxonomy, we apply three heuristic approaches in verification module. As a result, we construct the largest Chinese taxonomy with high precision about 95% called CN-Probase. Our taxonomy has been deployed on Aliyun, with over 82 million API calls in six months.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2019.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1.
4 papers.
- 2022Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervisioncited by 4
- 2023GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluationcited by 1
- 2023Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instancescited by 0
- 2024Light Up the Shadows: Enhance Long-Tailed Entity Grounding with Concept-Guided Vision-Language Modelscited by 0
- 2024Light Up the Shadows: Enhance Long-Tailed Entity Grounding with Concept-Guided Vision-Language Models16 Jun 2024
- 2023Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances25 Oct 2023
- 2023GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation25 Mar 2023
- 2022Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision28 Mar 2022