Triple

T15381778
Position Surface form Disambiguated ID Type / Status
Subject Budjak E367820 entity
Predicate containsCity P294 FINISHED
Object Chornomorsk E236857 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: Chornomorsk | Statement: [Budjak, containsCity, Chornomorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chornomorsk
Context triple: [Budjak, containsCity, Chornomorsk]
  • A. Chornomorske
    Chornomorske is a coastal settlement in western Crimea known for its location on the Black Sea and its role as a local resort and fishing community.
  • B. 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.
  • C. Mykolaiv
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • D. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • E. Port of Chornomorsk chosen
    The Port of Chornomorsk is a major Ukrainian Black Sea seaport and transport hub near Odesa, handling significant cargo and passenger traffic.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e61928c81908852c355d537ed9c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b5bc43c81908ffdb7819e3660d9 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:19 a.m.