Triple

T18290527
Position Surface form Disambiguated ID Type / Status
Subject Beslan E438099 entity
Predicate hasAirportNearby P4363 FINISHED
Object Beslan 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: Beslan Airport | Statement: [Beslan, hasAirportNearby, Beslan Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beslan Airport
Context triple: [Beslan, hasAirportNearby, Beslan Airport]
  • A. Beslan Airport chosen
    Beslan Airport is a regional airport serving the city of Vladikavkaz and the surrounding area in the Republic of North Ossetia–Alania, Russia.
  • B. Grozny Airport
    Grozny Airport is the main civil aviation airport serving the city of Grozny and the surrounding region in the Chechen Republic, Russia.
  • C. Kazan International Airport
    Kazan International Airport is the main commercial airport serving the city of Kazan and the surrounding region in Tatarstan, Russia.
  • D. Tolmachevo Airport
    Tolmachevo Airport is a major international airport in Novosibirsk, Russia, serving as a key air transport hub for Siberia and a primary base for several Russian airlines.
  • E. Karshi Airport
    Karshi Airport is a regional airport serving the city of Karshi in southern Uzbekistan, handling domestic flights and connecting the area to other parts of the country.
  • 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_69d8b914530c8190b4474d862a2b2a1b completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e500fee5248190928e68ddaa4d90d7 completed April 19, 2026, 4:21 p.m.
Created at: April 10, 2026, 10:35 a.m.