Triple

T18814503
Position Surface form Disambiguated ID Type / Status
Subject Kolinda Grabar-Kitarović E460100 entity
Predicate givenName P17 FINISHED
Object Kolinda NE NERFINISHED

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: Kolinda | Statement: [Kolinda Grabar-Kitarović, givenName, Kolinda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kolinda
Context triple: [Kolinda Grabar-Kitarović, givenName, Kolinda]
  • A. Kolinda Grabar-Kitarović chosen
    Kolinda Grabar-Kitarović is a Croatian politician and diplomat who served as the country’s first female president and previously held senior roles in both national government and NATO.
  • B. Melania Knauss
    Melania Knauss is a Slovenian-American former fashion model best known as the wife of Donald Trump and former First Lady of the United States.
  • C. Dimitra Priebus
    Dimitra Priebus is the mother of American attorney and former White House Chief of Staff Reince Priebus.
  • D. Ankica Tuđman
    Ankica Tuđman was the First Lady of Croatia and the wife of the country’s first president, Franjo Tuđman.
  • E. Pamela Habibović
    Pamela Habibović is a Dutch scientist and academic leader who serves as rector magnificus of Maastricht University.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3df2d3881909b336d813bbfd0aa completed April 20, 2026, 3:56 a.m.
Created at: April 10, 2026, 11:53 a.m.