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Related Questions
- What are the main sources of ambiguity in entity disambiguation for complex knowledge graph-based models like Qwen?
- How do contextual clues and linguistic features impact entity disambiguation in Qwen and similar models?
- What are the key challenges in handling homographs, homophones, and polysemous words in entity disambiguation for Qwen?
- How can Qwen and other complex knowledge graph-based models handle the problem of entity overlap and synonymy?
- What role does background knowledge play in entity disambiguation for Qwen and other complex knowledge graph-based models?
- How can Qwen and similar models handle the challenge of entity evolution over time, such as changes in entity meaning or scope?
- What are the key differences in entity disambiguation approaches for Qwen and other complex knowledge graph-based models, and how do they impact performance?
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