Triple

T12664854
Position Surface form Disambiguated ID Type / Status
Subject Melitopol E302522 entity
Predicate hasRoadConnectionTo P11435 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: [Melitopol, hasRoadConnectionTo, Mariupol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariupol
Context triple: [Melitopol, hasRoadConnectionTo, 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. Bucha
    Bucha is a suburban town northwest of Kyiv in northern Ukraine, internationally known as the site of alleged war crimes and civilian massacres during the 2022 Russian invasion.
  • E. Melitopol
    Melitopol is a strategically important industrial and transportation hub in southeastern Ukraine, known for its agricultural production and key road and rail connections.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617e030881908444743b8a7e0d75 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbb4d0088190b71fc0573cd40ddd completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:19 p.m.