Triple

T3536828
Position Surface form Disambiguated ID Type / Status
Subject The Lego Movie E74791 entity
Predicate mainCharacter P1183 FINISHED
Object Emmet Brickowski E148846 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: Emmet Brickowski | Statement: [The Lego Movie, mainCharacter, Emmet Brickowski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emmet Brickowski
Context triple: [The Lego Movie, mainCharacter, Emmet Brickowski]
  • A. Emmet Brickowski chosen
    Emmet Brickowski is the optimistic everyman construction worker who becomes an unlikely hero and "Special" in the animated film *The Lego Movie*.
  • B. Matthew Skemp
    Matthew Skemp is a musician best known as a member of the experimental indie rock band Volcano Choir.
  • C. Luke Brattan
    Luke Brattan is an Australian professional footballer and midfielder known for his playmaking ability in the A-League.
  • D. Nathan Maloney
    Nathan Maloney is a central teenage character in the British TV drama "Queer as Folk," known for exploring his sexuality and identity within Manchester’s gay scene.
  • E. Ryan Brant
    Ryan Brant was an American businessman best known as the founding CEO of video game publisher Take-Two Interactive, the company behind major franchises like Grand Theft Auto.
  • 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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbcc7b92481908d2d99948780f4d0 completed March 8, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48823ca248190a34d2d0eb3a496a7 completed March 13, 2026, 9:56 p.m.
Created at: March 8, 2026, 3:20 p.m.