Triple

T21380148
Position Surface form Disambiguated ID Type / Status
Subject Prostějov E527327 entity
Predicate hasTwinTown P919 FINISHED
Object Ivano-Frankivsk NE NERFINISHED

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: Ivano-Frankivsk | Statement: [Prostějov, hasTwinTown, Ivano-Frankivsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivano-Frankivsk
Context triple: [Prostějov, hasTwinTown, Ivano-Frankivsk]
  • A. Ivano-Frankivsk chosen
    Ivano-Frankivsk is a historic city in western Ukraine known as a cultural, economic, and administrative center of the Carpathian region.
  • B. 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.
  • C. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • D. Vinnytsia
    Vinnytsia is a major city in central Ukraine known as an important administrative, economic, and cultural center on the Southern Bug River.
  • E. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0cdab8c8190a7eebe6e5961ee75 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:11 p.m.