Triple

T16497327
Position Surface form Disambiguated ID Type / Status
Subject Bronisław Kaper E400717 entity
Predicate notableWork P4 FINISHED
Object Lili E236631 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: Lili | Statement: [Bronisław Kaper, notableWork, Lili]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lili
Context triple: [Bronisław Kaper, notableWork, Lili]
  • A. Lili chosen
    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.
  • B. Lili
    Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lilli
    Lilli is a feminine given name, often used in German-speaking and other European countries, and famously borne by the actress Lilli Palmer.
  • D. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • E. Lila
    Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e343a7c81909e04cbaaa40e2531 completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582a316c81908ec32679c976ba23 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:14 a.m.