Triple

T2098151
Position Surface form Disambiguated ID Type / Status
Subject Southern Ukraine E37029 entity
Predicate hasMajorCity P316 FINISHED
Object Mariupol E54211 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: Mariupol | Statement: [Southern Ukraine, hasMajorCity, Mariupol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariupol
Context triple: [Southern Ukraine, hasMajorCity, Mariupol]
  • A. Mariupol chosen
    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.
  • B. Kramatorsk
    Kramatorsk is an industrial city in eastern Ukraine that has become a key administrative and strategic center in the Donbas region.
  • C. Donetsk
    Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
  • D. Kherson
    Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
  • E. Mykolaiv
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba9de75c81909770409b5ae62c24 completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce742d288190bfdcffb81c29a173 completed March 10, 2026, 7:55 a.m.
Created at: March 4, 2026, 7:43 p.m.