Unverified50% confidenceFactExact time
Information Extraction is a classic task in natural language processing, whose goal is to identify entities, attributes, and relations from unstructured text and convert them into structured fields; traditional approaches rely on rule templates or sequence labeling models, while extraction based on large models typically uses prompting plus structured output.
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Long-term
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10/16/2026
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UnverifiedThe process of converting unstructured text into structured data is called Information Extraction in the field of NLP.80% similarUnverifiedDify's Parameter Extractor node receives unstructured or semi-structured text and uses a large model to extract target information according to predefined field names and types, storing the results in variables.73% similarUnverifiedStructured fact extraction is the process of converting unstructured natural language dialogue into a normalized data representation that can be stored, queried, and reasoned over by programs; it is usually accomplished with large language models, and the output format is mostly key-value pairs, triples, or JSON objects.67% similarUnverified语义检索技术通过嵌入模型将Skill描述文本转化为高维向量存入向量数据库，通过余弦相似度等算法检索最匹配的技能67% similarUnverifiedThe complete flow of this workflow is: natural language input → location parsing → data search → conditional filtering → structured storage.66% similar
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