Triple

T9152383
Position Surface form Disambiguated ID Type / Status
Subject LuLu E219617 entity
Predicate hasCapitalizationVariant P12011 FINISHED
Object LULU E41999 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: LULU | Statement: [LuLu, hasCapitalizationVariant, LULU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LULU
Context triple: [LuLu, hasCapitalizationVariant, LULU]
  • A. Lulu chosen
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • B. Lulu Bett
    Lulu Bett is the central character of Zona Gale's Pulitzer Prize-winning novel "Miss Lulu Bett," a quiet, self-effacing Midwestern woman whose constrained life and unexpected marriage spark a journey toward independence and self-realization.
  • C. Luli
    Luli is a dialect of the Paama language, spoken by a subset of Paama speakers in Vanuatu.
  • D. Lala
    Lala is an Indian honorific title traditionally used as a respectful prefix for educated or distinguished men, particularly in North India.
  • E. Lali
    Lali is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca96cf4548190a3a45172f0e9d0ec completed April 1, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05bfe53808190ac4cb24823b886d3 completed April 4, 2026, 12:31 a.m.
Created at: March 30, 2026, 7:20 p.m.