Triple

T14876229
Position Surface form Disambiguated ID Type / Status
Subject VOHS E349873 entity
Predicate replacedAirport P29669 FINISHED
Object Begumpet Airport E350663 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: Begumpet Airport | Statement: [VOHS, replacedAirport, Begumpet Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Begumpet Airport
Context triple: [VOHS, replacedAirport, Begumpet Airport]
  • A. Begumpet Airport chosen
    Begumpet Airport is the former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
  • B. Gaggal Airport
    Gaggal Airport is a domestic airport serving the Kangra district and the Dharamshala region in the Indian state of Himachal Pradesh.
  • C. Ranai Airport
    Ranai Airport is the main civil and military airport serving the remote Natuna Islands in Indonesia’s Riau Islands province.
  • D. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • E. 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.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e3e5d48190a132f2cf012b01e2 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dbf1f5c8190ad4626d14e0d8109 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:55 a.m.