Triple

T13594543
Position Surface form Disambiguated ID Type / Status
Subject Richard Hatch E324781 entity
Predicate name P16 FINISHED
Object Richard Hatch E324781 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Richard Hatch | Statement: [Richard Hatch, name, Richard Hatch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Hatch
Context triple: [Richard Hatch, name, Richard Hatch]
  • A. Richard Hatch chosen
    Richard Hatch was an American actor best known for his roles in the television series Battlestar Galactica and various other TV dramas of the 1970s and 1980s.
  • B. Michael Biehn
    Michael Biehn is an American actor best known for his roles in science fiction and action films such as The Terminator, Aliens, and The Abyss.
  • C. Lance Kerwin
    Lance Kerwin was an American actor best known for his prominent roles in 1970s television dramas and horror projects, particularly as a teen protagonist.
  • D. Chris Hargensen
    Chris Hargensen is a central antagonist in Stephen King’s novel "Carrie," known as a cruel high school bully whose actions help trigger the story’s catastrophic climax.
  • E. Kirk Baxter
    Kirk Baxter is an Australian film editor best known for his Academy Award–winning collaborations with director David Fincher on films such as "The Social Network" and "The Girl with the Dragon Tattoo."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc762a08190b5d29cef9923da84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.