Triple

T599333
Position Surface form Disambiguated ID Type / Status
Subject Petro Poroshenko E11457 entity
Predicate residence P75 FINISHED
Object Kyiv, Ukraine E17733 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: Kyiv, Ukraine | Statement: [Petro Poroshenko, residence, Kyiv, Ukraine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyiv, Ukraine
Context triple: [Petro Poroshenko, residence, Kyiv, Ukraine]
  • A. Kyiv chosen
    Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
  • B. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • C. Dnipro
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • D. Odesa
    Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
  • E. Mariupol
    Mariupol is a major industrial city in southeastern Ukraine known for its strategic port on the Sea of Azov and its significant role in recent military conflicts.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d78c0f08190b83ad89062ccb0b9 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a51f37f8748190bff705fd2bbc489c completed March 2, 2026, 5:25 a.m.
Created at: March 1, 2026, 7:35 p.m.