Triple

T5775810
Position Surface form Disambiguated ID Type / Status
Subject Reichskommissariat Ukraine E127437 entity
Predicate capital P234 FINISHED
Object Rivne E226359 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: Rivne | Statement: [Reichskommissariat Ukraine, capital, Rivne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rivne
Context triple: [Reichskommissariat Ukraine, capital, Rivne]
  • A. Rivne chosen
    Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
  • B. Vinnytsia
    Vinnytsia is a major city in central Ukraine known as an important administrative, economic, and cultural center on the Southern Bug River.
  • 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. Drohobych
    Drohobych is a historic city in western Ukraine known for its medieval architecture, salt production heritage, and association with writer and artist Bruno Schulz.
  • E. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial center.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029de3bb4819087a6f3e920e12990 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c124ef1c3c8190a2302fc0ce9b8324 completed March 23, 2026, 11:33 a.m.
Created at: March 22, 2026, 3:50 p.m.