Fact extraction: structured data from unstructured text

Beyond tagging documents with concepts, Semaphore can extract structured facts from unstructured content. This includes:

• Named entities: People, organizations, locations

• Quantities: Dates, monetary values, percentages

• Relationships: "Company A acquired Company B for $X"

Fact extraction is powered by:

• Natural Language Processing (NLP): Tokenization, part-of-speech tagging, and pattern recognition

• Semantic rules: Context-aware logic that understands how entities relate

Use Cases:

• Extracting parties and amounts from contracts

• Identifying adverse events in clinical trial reports

• Capturing customer names and complaint types from support tickets