Triple

T2044836
Position Surface form Disambiguated ID Type / Status
Subject Black Sea Governorate E45426 entity
Predicate capital P234 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: [Black Sea Governorate, capital, Novorossiysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novorossiysk
Context triple: [Black Sea Governorate, capital, 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. Gelendzhik
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • C. 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.
  • D. Novocherkassk
    Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
  • E. 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.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9728f688190939d7c4df524f9b4 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69af8342b7688190a626b4f5d3b3807d completed March 10, 2026, 2:34 a.m.
Created at: March 4, 2026, 7:39 p.m.