Triple

T8294228
Position Surface form Disambiguated ID Type / Status
Subject Tina Kotek E194174 entity
Predicate name P16 FINISHED
Object Tina Kotek E194174 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: Tina Kotek | Statement: [Tina Kotek, name, Tina Kotek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tina Kotek
Context triple: [Tina Kotek, name, Tina Kotek]
  • A. Tina Kotek chosen
    Tina Kotek is an American politician and former state legislative leader who became the first openly lesbian governor in the United States.
  • B. Connie Snyder
    Connie Snyder is an American philanthropist and co-founder of the Ballmer Group, known for her work supporting children’s welfare, education, and social services.
  • C. Sally Priebus
    Sally Priebus is the wife of American attorney and political figure Reince Priebus, former White House Chief of Staff and Republican National Committee chairman.
  • D. Christine Peterson
    Christine Peterson is a futurist and technology activist best known for co-founding the Foresight Institute and promoting nanotechnology and responsible technological development.
  • E. Christine Weiss
    Christine Weiss is known as the wife of French politician Gérard Larcher, longtime President of the French Senate.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df5fff88190ac51a8d1c3eb2fe2 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1ce5a0c881909ee517678cdc4ef2 completed April 2, 2026, 7:38 a.m.
Created at: March 30, 2026, 5:52 p.m.