Triple

T17917466
Position Surface form Disambiguated ID Type / Status
Subject James P. "Sulley" Sullivan E447969 entity
Predicate guardianOf P1040 FINISHED
Object Boo NE NERFINISHED

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: Boo | Statement: [James P. "Sulley" Sullivan, guardianOf, Boo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boo
Context triple: [James P. "Sulley" Sullivan, guardianOf, Boo]
  • A. Boo
    Boo is a statically typed, Python-inspired programming language for the .NET platform that was once used as a primary scripting option in the Unity game engine.
  • B. Boo
    Boo is the reclusive, mysterious neighbor in Harper Lee’s novel "To Kill a Mockingbird," whose true kindness is revealed over the course of the story.
  • C. Boo
    Boo is a suburban district and island area in the Stockholm archipelago, located within Nacka Municipality in Sweden.
  • D. Boo chosen
    Boo is the young human girl in Pixar's animated film "Monsters, Inc." whose unexpected arrival in the monster world drives the story's central conflict and emotional core.
  • E. Boo
    Boo is a recurring ghost-like enemy in the Super Mario series, known for covering its face when looked at and attacking when the player’s back is turned.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a30778fc81908b5b2e308fb158a5 completed April 19, 2026, 9:40 a.m.
Created at: April 10, 2026, 10:20 a.m.