Triple

T4182295
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg Oblast E88221 entity
Predicate contains P35 FINISHED
Object Kommunar E297652 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: Kommunar | Statement: [Saint Petersburg Oblast, contains, Kommunar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kommunar
Context triple: [Saint Petersburg Oblast, contains, Kommunar]
  • A. Kommunar chosen
    Kommunar is a small town in Leningrad Oblast, Russia, known for its location along the Izhora River southeast of Saint Petersburg.
  • B. Diass
    Diass is a commune in western Senegal that hosts the country’s main international gateway, Blaise Diagne International Airport.
  • C. Rana Municipality
    Rana Municipality is a local government area in Nordland county, Norway, encompassing the town of Mo i Rana and surrounding districts.
  • D. Romita Municipality
    Romita Municipality is an administrative region in the state of Guanajuato, Mexico, known for its agricultural activities and location within the Bajío area.
  • E. Murça Municipality
    Murça Municipality is a local administrative region in northern Portugal known for its rural landscapes, wine production, and historical heritage.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0305e2e88190a51f176f8534f1f9 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589fbcc5881908f245bb377082dcc completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:45 p.m.