Triple

T10982890
Position Surface form Disambiguated ID Type / Status
Subject Central Federal Okrug E259552 entity
Predicate includesCity P3207 FINISHED
Object Belgorod E282740 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: Belgorod | Statement: [Central Federal Okrug, includesCity, Belgorod]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belgorod
Context triple: [Central Federal Okrug, includesCity, Belgorod]
  • A. Belgorod chosen
    Belgorod is a city in western Russia near the Ukrainian border, historically significant as a strategic site of major World War II battles and offensives.
  • B. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • C. Oryol
    Oryol was a notable warship of the Imperial Russian Navy, recognized for its role in Russia’s early modern naval history.
  • D. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • E. Belgorod region
    The Belgorod region is an area in western Russia near the Ukrainian border, historically notable as a major World War II battleground and now an important agricultural and industrial region.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d772eb518c8190a885a417815f2ff6 completed April 9, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e6e19c9c81909d114cf9bd0e2f84 completed April 21, 2026, 2:54 a.m.
Created at: April 8, 2026, 9:24 p.m.