Triple

T7580139
Position Surface form Disambiguated ID Type / Status
Subject Bobbi Kristina Brown E179463 entity
Predicate hasPartInName P5298 FINISHED
Object Kristina E368674 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: Kristina | Statement: [Bobbi Kristina Brown, hasPartInName, Kristina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristina
Context triple: [Bobbi Kristina Brown, hasPartInName, Kristina]
  • A. Kristina chosen
    Kristina is a feminine given name commonly used in various European countries, often considered a variant of Christina.
  • B. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • C. Kristina Lugn
    Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
  • D. Christina Regina Siöberg
    Christina Regina Siöberg was the Swedish-born wife of Russian military engineer and nobleman Abram Petrovich Gannibal, making her an ancestor of the writer Alexander Pushkin.
  • E. Katarina Frostenson
    Katarina Frostenson is a Swedish poet, writer, and former member of the Swedish Academy known for her influential and experimental contributions to contemporary Swedish literature.
  • 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_69c6f975bbc08190aec30f902eaea494 completed March 27, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861735c7c81908e2c9fcbb1005ec3 completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:52 p.m.