Triple

T1201756
Position Surface form Disambiguated ID Type / Status
Subject Krasnodar Krai E25796 entity
Predicate hasCity P316 FINISHED
Object Tuapse E166972 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: Tuapse | Statement: [Krasnodar Krai, hasCity, Tuapse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuapse
Context triple: [Krasnodar Krai, hasCity, Tuapse]
  • A. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • B. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • C. Gelendzhik chosen
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • D. Arkhangelsk
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • E. Kerch
    Kerch is a historic port city in eastern Crimea, strategically located on the Kerch Strait linking the Black Sea and the Sea of Azov.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9fece4819089a6a2d61e61fa2e completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad8a9f91808190b44715dc3df31cc3 completed March 8, 2026, 2:41 p.m.
Created at: March 1, 2026, 7:46 p.m.