Triple

T10542519
Position Surface form Disambiguated ID Type / Status
Subject Port of Mariupol E248730 entity
Predicate nearbyCity P350 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: [Port of Mariupol, nearbyCity, Mariupol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariupol
Context triple: [Port of Mariupol, nearbyCity, 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5190f46d08190a92b1191881ffb92 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b23b2988190b536d5ecb76298ff completed April 10, 2026, 7:10 p.m.
Created at: April 6, 2026, 12:32 p.m.