Triple

T9109548
Position Surface form Disambiguated ID Type / Status
Subject Arkhangelsk E218560 entity
Predicate isServedBy P1293 FINISHED
Object Talagi Airport E466429 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: Talagi Airport | Statement: [Arkhangelsk, isServedBy, Talagi Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talagi Airport
Context triple: [Arkhangelsk, isServedBy, Talagi Airport]
  • A. Talagi Airport chosen
    Talagi Airport is the main commercial airport serving the city of Arkhangelsk in northwestern Russia.
  • B. Tambolaka Airport
    Tambolaka Airport is a regional airport serving the western part of Sumba Island in East Nusa Tenggara, Indonesia, providing domestic connections to major Indonesian cities.
  • C. Savusavu Airport
    Savusavu Airport is a small domestic airport serving the town of Savusavu on the Fijian island of Vanua Levu.
  • D. Butaritari Airport
    Butaritari Airport is a small public airfield serving the island of Butaritari in Kiribati, providing vital domestic air connections for the local population.
  • E. Beni Airport
    Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
  • 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_69ca83db7448819090d0a5de842ef2ac completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca845d9b0819084230e7cdd92dee0 completed April 1, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05bf002c081909bb82bb765bbf4b1 completed April 4, 2026, 12:31 a.m.
Created at: March 30, 2026, 7:16 p.m.