Summary of Dynamicner: a Dynamic, Multilingual, and Fine-grained Dataset For Llm-based Named Entity Recognition, by Hanjun Luo et al.
DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition
by Hanjun Luo, Yingbin Jin, Xinfeng Li, Xuecheng Liu, Ruizhe Chen, Tong Shang, Kun Wang, Qingsong Wen, Zuozhu Liu
First submitted to arxiv on: 17 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes DynamicNER, a novel Named Entity Recognition (NER) dataset designed specifically for Large Language Models (LLMs), which addresses the limitations of existing datasets. The DynamicNER dataset features dynamic categorization, multilingual support for 8 languages, and covers 155 entity types across multiple domains. To overcome the issues faced by LLM-based NER methods, the authors introduce CascadeNER, a two-stage strategy leveraging lightweight LLMs. Experimental results demonstrate that DynamicNER is an effective benchmark for LLM-based NER methods, while CascadeNER outperforms existing approaches with reduced computational resources. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Named Entity Recognition (NER) uses Large Language Models (LLMs) to find important information like names, locations, and organizations in text. The problem is that current datasets aren’t designed well for LLMs, making it hard to evaluate models or fine-tune them. This paper solves the issue by creating a new dataset called DynamicNER. It’s made specifically for LLMs and has features like dynamic categorization, support for 8 languages, and covers many types of entities across different topics. The authors also developed a new method called CascadeNER that uses lightweight LLMs to improve NER performance while using less computer power. |
Keywords
» Artificial intelligence » Named entity recognition » Ner
