Triple

T2405799
Position Surface form Disambiguated ID Type / Status
Subject The Wizard of Oz E50273 entity
Predicate helpsCharacter P7748 FINISHED
Object Scarecrow E48999 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: Scarecrow | Statement: [The Wizard of Oz, helpsCharacter, Scarecrow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scarecrow
Context triple: [The Wizard of Oz, helpsCharacter, Scarecrow]
  • A. Scarecrow
    Scarecrow is a Batman supervillain and deranged psychiatrist who uses fear-inducing toxins to terrorize Gotham City.
  • B. The Scarecrow chosen
    The Scarecrow is a beloved fictional figure from L. Frank Baum’s Oz stories, known for his quest for a brain and his role as one of Dorothy’s loyal companions.
  • C. The Bat
    The Bat is a popular inverted boomerang-style roller coaster at Canada's Wonderland known for its intense forward and backward loops.
  • D. Robin
    Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
  • E. Boo
    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.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abd0d942048190bc5c715faa850632 completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef09b92048190acfa3a85417f259c completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:58 p.m.