Triple

T12375621
Position Surface form Disambiguated ID Type / Status
Subject Munger E295114 entity
Predicate hasNearbyAirport P4363 FINISHED
Object Gaya Airport E301314 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: Gaya Airport | Statement: [Munger, hasNearbyAirport, Gaya Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaya Airport
Context triple: [Munger, hasNearbyAirport, Gaya Airport]
  • A. Gaya Airport chosen
    Gaya Airport is an international airport in the Indian state of Bihar that primarily serves the city of Gaya and nearby Buddhist pilgrimage sites such as Bodh Gaya.
  • B. Begumpet Airport
    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former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
  • C. Awang Airport
    Awang Airport is a domestic airport serving the province of Maguindanao in the southern Philippines.
  • D. Diffa Airport
    Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
  • E. Baljek Airport
    Baljek Airport is a small regional airport serving the town of Tura and the surrounding Garo Hills region in the Indian state of Meghalaya.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fb8d6c081909e8bbbd52c73f29c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c648b948190bfc6032cf8fdd7d5 completed May 2, 2026, 10:36 p.m.
Created at: April 8, 2026, 9:54 p.m.