Triple

T12134928
Position Surface form Disambiguated ID Type / Status
Subject Toni Lawrence E289031 entity
Predicate notableWork P4 FINISHED
Object Baretta E855830 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: Baretta | Statement: [Toni Lawrence, notableWork, Baretta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baretta
Context triple: [Toni Lawrence, notableWork, Baretta]
  • A. Baretta chosen
    Baretta is a 1970s American television crime drama series centered on an unconventional undercover police detective.
  • B. Luella Gear
    Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
  • C. Fusco
    Fusco is a character in the crime drama film "Dinner Rush," involved in the tense, interwoven events surrounding a New York City restaurant.
  • D. Agent 13
    Agent 13 is the codename of Sharon Carter, a highly skilled S.H.I.E.L.D. operative and frequent ally of Captain America in Marvel Comics.
  • E. Agent 13
    Agent 13 is the covert alias used by James Wilkinson, a character known as a skilled undercover operative in the Marvel universe.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158c59e0819094d4522a107482b2 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f68eab98819086a480a90312c3fe completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.