Triple

T17535780
Position Surface form Disambiguated ID Type / Status
Subject Cherkasy Uyezd E427055 entity
Predicate namedAfter P63 FINISHED
Object Cherkasy 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: Cherkasy | Statement: [Cherkasy Uyezd, namedAfter, Cherkasy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cherkasy
Context triple: [Cherkasy Uyezd, namedAfter, Cherkasy]
  • A. Cherkasy chosen
    Cherkasy is a city in central Ukraine located on the banks of the Dnieper River and serving as an important regional industrial and cultural center.
  • B. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • C. Lutsk
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • D. Rivne
    Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
  • E. Zhytomyr
    Zhytomyr is a historic city in northwestern Ukraine known as an important regional center and the birthplace of pioneering rocket engineer Sergei Korolev.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4536b8d6c8190906314708001a830 completed April 19, 2026, 4 a.m.
Created at: April 10, 2026, 5:49 a.m.