Triple

T7255701
Position Surface form Disambiguated ID Type / Status
Subject Black Sea coast E157716 entity
Predicate hasMajorPort P942 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 coast, hasMajorPort, Novorossiysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novorossiysk
Context triple: [Black Sea coast, hasMajorPort, 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. Volgodonsk
    Volgodonsk is an industrial city in southwestern Russia known for its nuclear power plant and location on the Tsimlyansk Reservoir in Rostov Oblast.
  • D. Zheleznovodsk
    Zheleznovodsk is a spa town in Russia’s Stavropol Krai, known for its mineral springs and health resorts in the Caucasus region.
  • E. 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.
  • 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6eaa0c76c81909fe43ed6938a13ea completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3b053248190802b11212a8a668f completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:56 p.m.