Triple

T12838731
Position Surface form Disambiguated ID Type / Status
Subject Sumy Oblast E306986 entity
Predicate containsCity P294 FINISHED
Object Krolevets E1009532 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: Krolevets | Statement: [Sumy Oblast, containsCity, Krolevets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krolevets
Context triple: [Sumy Oblast, containsCity, Krolevets]
  • A. Krolevets chosen
    Krolevets is a small historic city in northeastern Ukraine known for its traditional weaving crafts and location within Sumy Oblast.
  • B. Dupnitsa
    Dupnitsa is a town in southwestern Bulgaria known as a regional center near the Osogovo Mountains, with historical roots and access to mountain tourism and outdoor activities.
  • C. Tsarevo
    Tsarevo is a coastal town and popular seaside resort on the Black Sea in southeastern Bulgaria.
  • D. Berestovitsa
    Berestovitsa is a Belarusian town known for its strategic location near the border with Poland, serving as an important regional transport and customs point.
  • E. Karmanovo
    Karmanovo is a rural village located within the Gagarinsky District of Smolensk Oblast in western Russia.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff11b4481909fb2f92c46186853 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af4f56108190b75dbf9bb144e94a completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:35 p.m.