Fact extraction pulls specific assertions out of unstructured text and represents them in a structured form: the event, its date, the participants, and the source location. It goes beyond identifying entities to capturing what occurred.
Extracted facts become the raw material for chronologies, issue analysis, and contradiction detection.
Alternative Names:
Automated Fact Extraction, Fact Mining
Why it Matters?
Facts are what litigation runs on, and they are scattered across records in inconsistent language and formats. Extracting them into a structured layer is what allows the same underlying work to produce a chronology, a witness outline, and a damages summary without three separate passes through the file. Extraction errors propagate into everything downstream, which is why validation against known-answer samples is essential before relying on it.
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Related terms
Frequently asked questions
How is fact extraction different from entity extraction?
Why do extraction errors matter more than summary errors?
