Triple

T17292158
Position Surface form Disambiguated ID Type / Status
Subject Randall Poster E419809 entity
Predicate notableWork P4 FINISHED
Object Aviator E54662 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: Aviator | Statement: [Randall Poster, notableWork, Aviator]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aviator
Context triple: [Randall Poster, notableWork, Aviator]
  • A. Aviatorilor
    Aviatorilor is a Bucharest Metro station serving the Aviatorilor area near Herăstrău Park in Romania’s capital.
  • B. Aviadores
    Aviadores is the popular nickname of Bolivian football club Jorge Wilstermann, alluding to its historic ties to aviation.
  • C. Aviators
    Aviators is a Minor League Baseball team based in the Las Vegas area, serving as the Triple-A affiliate of the Oakland Athletics.
  • D. The Aviator chosen
    The Aviator is a biographical drama film that chronicles the life and career of eccentric aviation pioneer and filmmaker Howard Hughes, portrayed by Leonardo DiCaprio.
  • E. Dogfight
    Dogfight is a stage musical with music and lyrics by Benj Pasek and Justin Paul, adapted from the 1991 film about a Marine’s last night before deployment in 1963 San Francisco.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e4378438508190924f732ad748b4d0 completed April 19, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a017959ffb0819099d70ed1541158ee completed May 11, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:40 a.m.