Triple

T4026725
Position Surface form Disambiguated ID Type / Status
Subject Relativity Media E83607 entity
Predicate hasKeyPerson P256 FINISHED
Object Tucker Tooley E321063 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: Tucker Tooley | Statement: [Relativity Media, hasKeyPerson, Tucker Tooley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tucker Tooley
Context triple: [Relativity Media, hasKeyPerson, Tucker Tooley]
  • A. Tucker Tooley chosen
    Tucker Tooley is an American film producer and executive known for backing commercially successful action and thriller movies in Hollywood.
  • B. Tim Latta
    Tim Latta is a soccer executive best known for serving as the general manager of the early Major League Soccer club Kansas City Wiz (now Sporting Kansas City).
  • C. Steven M. Tipton
    Steven M. Tipton is an American sociologist of religion and ethics known for his collaborative work on the role of religion and moral values in contemporary American life.
  • D. Trent Luckinbill
    Trent Luckinbill is an American film producer known for working on acclaimed movies such as the crime thriller "Sicario."
  • E. Brad Lander
    Brad Lander is an American politician and progressive Democrat who serves as the New York City Comptroller and previously represented Brooklyn in the New York City Council.
  • 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaed37e48190844032e7e77163e0 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556325c48819099d4cb5c2049d7e7 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:36 p.m.