Triple

T9866530
Position Surface form Disambiguated ID Type / Status
Subject Taurida Governorate E239845 entity
Predicate majorCity P316 FINISHED
Object Feodosiya E12601 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: Feodosiya | Statement: [Taurida Governorate, majorCity, Feodosiya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Feodosiya
Context triple: [Taurida Governorate, majorCity, Feodosiya]
  • A. Feodosia chosen
    Feodosia is a historic port city on the southeastern coast of Crimea, known for its Black Sea beaches, medieval fortifications, and association with painter Ivan Aivazovsky.
  • B. Yevpatoria
    Yevpatoria is a historic resort and port city on the western coast of Crimea, known for its beaches, therapeutic mud treatments, and diverse cultural heritage.
  • C. Sevastopol
    Sevastopol is a major port city on the Black Sea, historically significant as a naval base and the site of key military conflicts.
  • D. Simferopol–Alushta
    Simferopol–Alushta is the central mountain-crossing section of the Crimean trolleybus route that links the regional capital Simferopol with the Black Sea resort town of Alushta.
  • E. Simferopol
    Simferopol is the administrative and cultural center of Crimea, known as a key regional hub for transportation, education, and industry.
  • 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_69ca84e7506c819095cbde4ff16512bb completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3d091e48190b10463562d0dc461 completed April 2, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d22886b2388190a4320eeb81f3e433 completed April 5, 2026, 9:16 a.m.
Created at: March 30, 2026, 8:36 p.m.