Triple

T7577529
Position Surface form Disambiguated ID Type / Status
Subject Disney animated features E179395 entity
Predicate notableWork P4 FINISHED
Object Tangled E70009 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: Tangled | Statement: [Disney animated features, notableWork, Tangled]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tangled
Context triple: [Disney animated features, notableWork, Tangled]
  • A. Tangled chosen
    Tangled is a 2010 Disney animated musical fantasy film that reimagines the Rapunzel fairy tale with a blend of comedy, adventure, and computer-generated animation.
  • B. Enchanted
    Enchanted is a 2007 Disney live-action/animated musical fantasy film that playfully subverts classic fairy-tale tropes as an animated princess is transported into modern-day New York City.
  • C. Enchanted
    "Enchanted" is a popular 1959 doo-wop ballad by The Platters, known for its romantic lyrics and smooth vocal harmonies.
  • D. Blancanieves
    Blancanieves is a 2012 Spanish silent black-and-white fantasy drama film that reimagines the Snow White fairy tale in 1920s Spain.
  • E. Rapunzel
    Rapunzel is a classic fairy-tale princess best known for her extraordinarily long hair and her story of captivity in a tower and eventual escape.
  • 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_69c69f327db881909a21ae3b156f8ded completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f94cdbec81909f2ba7ce04e49931 completed March 27, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861673ae48190b86e8023fd02771c completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:51 p.m.