Triple

T11430748
Position Surface form Disambiguated ID Type / Status
Subject Friend Like Me E270871 entity
Predicate characterPerformedBy P1507 FINISHED
Object Genie E347351 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: Genie | Statement: [Friend Like Me, characterPerformedBy, Genie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genie
Context triple: [Friend Like Me, characterPerformedBy, Genie]
  • A. Genie chosen
    Genie is a powerful, wisecracking magical being from Disney's animated film "Aladdin," best known for granting wishes and his energetic, comedic personality.
  • B. Lili
    Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lili
    Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
  • D. Nana
    "Nana" is a popular hit single by Tanzanian Bongo Flava artist Diamond Platnumz, known for its romantic theme and widespread success across East Africa.
  • E. Nana
    Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c1bfb881909720c74fe0fa837f completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b8e212088190b611333d5de05757 completed April 20, 2026, 5:25 a.m.
Created at: April 8, 2026, 9:35 p.m.