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The NarraSpace framework links words in the transcript to named elements in the image and retrieves utterances related to predefined scene events, in order to construct traceable classification evidence.
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10/21/2026
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VerifiedContextual Retrieval was proposed by Anthropic; it prepends an LLM-generated contextual summary to each chunk so that the chunk retains the necessary background information even when separated from the original text.69% similarUnverifiedDrawing on the contextual retrieval approach proposed by Anthropic, adding contextual sentences improved both retrieval effectiveness and verification accuracy.67% similarUnverifiedInformation extraction for automatically constructing a knowledge graph from unstructured text primarily involves two sub-tasks: named entity recognition (NER) and relation extraction (RE).66% similarUnverifiedThe contextual retrieval technique involves prepending the document title and section path to each chunk before embedding, or using an LLM to generate a brief summary describing the chunk's position within the document.64% similarUnverifiedStructure-aware chunking uses headings and sections to preserve context; writing the heading path into the text that is embedded helps retrieval matching, and putting it into the context sent to the answer model helps the model understand semantics—these are different stages and cannot substitute for each other.64% similar
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