> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/information-extraction.md).

# Information Extraction

Evaluate how well LLMs extract information from text. Detect missed entities or relations and enhance precision.

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Exclusive to enterprise customers. [Contact us](https://calendly.com/nirmalya-raga/30min?month=2025-09) to activate this feature.
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RagaAI provides metrics for evaluating specific information extraction tasks, in order to quantify the quality and specificity of the retrieval of targeted information from the source documents. Here is a list of available metrics:

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[MINEA](/ragaai-catalyst/ragaai-metric-library/information-extraction/minea.md)
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[Subjective Question Correction](/ragaai-catalyst/ragaai-metric-library/information-extraction/subjective-question-correction.md)
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[Precision@K](/ragaai-catalyst/ragaai-metric-library/information-extraction/precision-k.md)
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[Chunk Relevance](/ragaai-catalyst/ragaai-metric-library/information-extraction/chunk-relevance.md)
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[Entity Co-occurrence](/ragaai-catalyst/ragaai-metric-library/information-extraction/entity-co-occurrence.md)
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[Fact Entropy](/ragaai-catalyst/ragaai-metric-library/information-extraction/fact-entropy.md)
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