Triple

T6240413
Position Surface form Disambiguated ID Type / Status
Subject Mykolaiv E139584 entity
Predicate hasAlternativeName P39 FINISHED
Object Mikolayiv E139584 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: Mikolayiv | Statement: [Mykolaiv, hasAlternativeName, Mikolayiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mikolayiv
Context triple: [Mykolaiv, hasAlternativeName, Mikolayiv]
  • A. Myrhorod
    Myrhorod is a historic city in central Ukraine, known for its mineral springs and as the setting of several stories by writer Nikolai Gogol.
  • B. Mykolaiv chosen
    Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • C. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • D. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • E. Melitopol
    Melitopol is a strategically important industrial and transportation hub in southeastern Ukraine, known for its agricultural production and key road and rail connections.
  • 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_69c008b1c5088190ae6de2555fc05ad8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063067d9c819085a18d9d03939266 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3e5bd988190ad9b0af668f5b05c completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:23 p.m.