Triple

T4560063
Position Surface form Disambiguated ID Type / Status
Subject I, Tonya E120570 entity
Predicate director P255 FINISHED
Object Craig Gillespie E117716 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: Craig Gillespie | Statement: [I, Tonya, director, Craig Gillespie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Craig Gillespie
Context triple: [I, Tonya, director, Craig Gillespie]
  • A. Craig Gillespie chosen
    Craig Gillespie is an Australian-American film director known for character-driven comedies and dramas such as "Lars and the Real Girl" and the biographical film "I, Tonya."
  • B. David O. Russell
    David O. Russell is an American filmmaker known for his offbeat, character-driven dramas and dark comedies such as The Fighter, American Hustle, and Three Kings.
  • C. Bennett Miller
    Bennett Miller is an American film director known for his critically acclaimed, character-driven dramas such as "Capote," "Moneyball," and "Foxcatcher."
  • D. Damien Chazelle
    Damien Chazelle is an American filmmaker and screenwriter known for his stylish, music-driven dramas such as "Whiplash" and the Oscar-winning "La La Land."
  • E. Paul Thomas Anderson
    Paul Thomas Anderson is an acclaimed American filmmaker known for his character-driven, stylistically distinctive films such as "Boogie Nights," "Magnolia," and "There Will Be Blood."
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd582b871c8190be0b70c76d639000 completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc593eaf881908a9043366230b391 completed March 20, 2026, 10:09 p.m.
Created at: March 20, 2026, 1:09 p.m.