Triple

T1201754
Position Surface form Disambiguated ID Type / Status
Subject Krasnodar Krai E25796 entity
Predicate hasCity P316 FINISHED
Object Novorossiysk E31261 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: Novorossiysk | Statement: [Krasnodar Krai, hasCity, Novorossiysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novorossiysk
Context triple: [Krasnodar Krai, hasCity, Novorossiysk]
  • A. Novorossiysk chosen
    Novorossiysk is a major port city on Russia’s Black Sea coast that serves as an important naval and commercial hub.
  • B. Taganrog
    Taganrog is a port city in southwestern Russia on the northern coast of the Sea of Azov, known for its maritime trade and as the birthplace of writer Anton Chekhov.
  • C. Berdyansk
    Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
  • D. Volgograd
    Volgograd is a major city in southwestern Russia on the Volga River, historically known as Stalingrad and renowned as the site of one of World War II’s most pivotal and brutal battles.
  • E. Rostov-on-Don
    Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
  • 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_69ad08a02ba081908e0036a9d8bfc9f2 completed March 8, 2026, 5:26 a.m.
Created at: March 1, 2026, 7:46 p.m.