Triple

T5228375
Position Surface form Disambiguated ID Type / Status
Subject One Little Spark E118047 entity
Predicate featuresCharacter P626 FINISHED
Object Dreamfinder E232223 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: Dreamfinder | Statement: [One Little Spark, featuresCharacter, Dreamfinder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dreamfinder
Context triple: [One Little Spark, featuresCharacter, Dreamfinder]
  • A. Dreamfinder chosen
    Dreamfinder is a whimsical, bearded explorer of imagination from Disney's Epcot, known for guiding guests through creative adventures alongside his dragon companion Figment.
  • B. Moonhaven
    Moonhaven is a science fiction television series set in a utopian lunar colony that becomes central to humanity’s survival.
  • C. City of Dreams
    City of Dreams is a popular nickname for Mumbai, reflecting its status as India’s financial hub and a magnet for people seeking opportunity and success.
  • D. Riverhouse
    Riverhouse is a luxury eco-friendly residential condominium building located in Manhattan’s Battery Park City neighborhood.
  • E. Haven
    "Haven" is a literary work by British writer and socialite Elizabeth Asquith, reflecting her early 20th-century intellectual and artistic milieu.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7adee36881909b034b8735db9d67 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef80ca924819095bcc729feb0e464 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:48 p.m.