Triple

T18457825
Position Surface form Disambiguated ID Type / Status
Subject Palam E450949 entity
Predicate hasNearbyAirport P4363 FINISHED
Object Palam 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: Palam Airport | Statement: [Palam, hasNearbyAirport, Palam Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palam Airport
Context triple: [Palam, hasNearbyAirport, Palam Airport]
  • A. Palam Airport chosen
    Palam Airport is the former name and original airfield of Delhi’s main international airport, now known as Indira Gandhi International Airport.
  • B. Phù Cát Airport
    Phù Cát Airport is a regional airport in Bình Định Province, Vietnam, serving the coastal city of Quy Nhơn and the surrounding area.
  • C. Naypyidaw International Airport
    Naypyidaw International Airport is the main commercial airport serving Myanmar’s capital, designed to handle international and domestic flights with modern terminal facilities.
  • D. 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.
  • E. Kalemie Airport
    Kalemie Airport is a public airport serving the town of Kalemie in the Tanganyika Province of the Democratic Republic of the Congo, providing regional air transport connections.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e52a7c18d88190ac17f58111722223 completed April 19, 2026, 7:18 p.m.
Created at: April 10, 2026, 11:31 a.m.