Triple

T15365713
Position Surface form Disambiguated ID Type / Status
Subject Kimberly J. Mueller E367407 entity
Predicate givenName P17 FINISHED
Object Kimberly E23752 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: Kimberly | Statement: [Kimberly J. Mueller, givenName, Kimberly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimberly
Context triple: [Kimberly J. Mueller, givenName, Kimberly]
  • A. Kimberly chosen
    Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
  • B. Kimberly
    Kimberly is a small city located in Idaho’s Magic Valley region, known for its agricultural surroundings and close proximity to Twin Falls.
  • C. Kelli
    Kelli is a feminine given name, typically considered a variant spelling of Kelly.
  • D. Karenna
    Karenna is an American lawyer, author, and environmental activist best known as the daughter of former U.S. Vice President Al Gore.
  • E. Kayely
    Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e497de48190be249b110999ec5c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b4cc39c81908a0aff959352f6d5 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:18 a.m.