Triple

T17841218
Position Surface form Disambiguated ID Type / Status
Subject Bulunsky District E445530 entity
Predicate hasTransport P1298 FINISHED
Object Tiksi Airport 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: Tiksi Airport | Statement: [Bulunsky District, hasTransport, Tiksi Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiksi Airport
Context triple: [Bulunsky District, hasTransport, Tiksi Airport]
  • A. Tiksi Airport chosen
    Tiksi Airport is a remote Arctic airport in northern Russia that serves the settlement of Tiksi and functions as a key regional and military airfield in the Sakha Republic.
  • B. Landvetter Airport
    Landvetter Airport is an international airport serving the Gothenburg region in western Sweden and is one of the country’s major aviation hubs.
  • C. Helsinki Airport
    Helsinki Airport is Finland’s main international air hub, located near Helsinki and serving as a major gateway between Europe and Asia.
  • D. Turku Airport
    Turku Airport is an international airport in southwestern Finland serving the city of Turku and the surrounding region with passenger and cargo flights.
  • E. Tampere–Pirkkala Airport
    Tampere–Pirkkala Airport is a Finnish international airport serving the Tampere region, handling both civilian air traffic and military operations.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2b2ea08190926ec0cf01285833 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.