Extract entities, relations, events, and triplets from text into Markdown tables.
npx skills add https://github.com/Hawksight-AI/semantica --skill extract-hawksight-ai
Please help me install this Agent Skill. Skill: extract Source: https://github.com/Hawksight-AI/semantica/tree/main/plugins/skills/extract Command: npx skills add https://github.com/Hawksight-AI/semantica --skill extract-hawksight-ai
This Skill automates comprehensive information extraction from documents or inline text, enabling efficient data parsing and analysis.
Input a text sample or file path into the command to see entities, relations, events, and triplets extracted and formatted as Markdown tables.
High-intent search queries and answers about installing and using this skill.
To extract structured information from unstructured text, use an NLP pipeline for named entity recognition, relation extraction, and event detection. This process identifies core semantic data and formats it into tables for immediate analysis.
Analyzing legal contracts for relationships is best handled by NLP extraction pipelines that detect named entities, events, and generate triplets. This reduces manual review time by validating extraction quality and highlighting data issues.
Yes, you can build a knowledge graph from document files by applying semantic extraction. The pipeline performs coreference resolution and triplet generation to map entities and relations, providing structured data for graph creation.
Semantic extraction supports coreference resolution and triplet generation through its NLP pipelines. These features map text references to specific entities and output structured relationship data for document analysis workflows.
To validate extraction quality when parsing large text blocks, use an NLP pipeline with built-in validation and reporting. It automatically highlights extraction issues to facilitate high-confidence data collection.
Information extraction from documents supports inline text samples and file paths as input. The pipeline processes these inputs to output extracted entities, relations, and events formatted as Markdown tables.
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microsoftBuild a knowledge graph from mixed files with an explicit audit trail.
ever-oliTokenize text with fast, Rust-backed NLP preprocessing for model training and inference.
jaechang-hitsExtract biomedical entities and answer questions from scientific literature using HuggingFace Transformers.
