Triple

T1760292
Position Surface form Disambiguated ID Type / Status
Subject Kamala Nehru E38641 entity
Predicate givenName P17 FINISHED
Object Kamala E130134 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: Kamala | Statement: [Kamala Nehru, givenName, Kamala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamala
Context triple: [Kamala Nehru, givenName, Kamala]
  • A. Kamala chosen
    Kamala is the given name of Kamala Harris, the 49th vice president of the United States and the first woman, first Black American, and first South Asian American to hold the office.
  • B. Leona Woods
    Leona Woods was an American physicist who, as one of the few women on the Manhattan Project, played a key role in the development and operation of the first nuclear reactor.
  • C. Sadiqa Kendi
    Sadiqa Kendi is an American pediatric emergency medicine physician and academic known for her work in child injury prevention and health equity.
  • D. Lynn Petra Alexander
    Lynn Petra Alexander is the birth name of Lynn Margulis, the influential American biologist best known for her work on the endosymbiotic theory of eukaryotic cell evolution.
  • E. Kimberly
    Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64410b58819098be7dc5da23d7af completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0ec80f48190bcdc92e5ed4e44e6 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.