Triple

T10601558
Position Surface form Disambiguated ID Type / Status
Subject Stuart Baird E275759 entity
Predicate notableWork P4 FINISHED
Object Maverick E517707 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: Maverick | Statement: [Stuart Baird, notableWork, Maverick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maverick
Context triple: [Stuart Baird, notableWork, Maverick]
  • A. Maverick
    Maverick is an MBTA subway station on Boston’s Blue Line serving the East Boston neighborhood.
  • B. Maverick
    Maverick is a political nickname for U.S. Senator John McCain, reflecting his reputation for independence and willingness to break with his party.
  • C. Maverick chosen
    Maverick is a 1994 comedic Western film starring Mel Gibson, Jodie Foster, and James Garner, centered on a charming gambler trying to raise money for a high-stakes poker tournament.
  • D. Maverick
    Maverick is a cigarette brand known for its budget-friendly positioning within the U.S. tobacco market.
  • E. Maverick
    Maverick is a classic American Western comedy television series that aired in the late 1950s, following the adventures of charming, poker-playing gambler Bret Maverick and his relatives.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6ded61d5c8190b13890c964b59949 completed April 8, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95ea8f1688190aa36e29b52667d26 completed April 10, 2026, 8:33 p.m.
Created at: April 8, 2026, 7:31 p.m.