Triple
T11827071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaya district |
E281283
|
entity |
| Predicate | hasAirport |
P105
|
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: [Gaya district, hasAirport, Gaya Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaya Airport Context triple: [Gaya district, hasAirport, 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former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.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.
Diffa Airport
Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
-
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.
Sunan Airport
Sunan Airport is the main international airport serving Pyongyang, the capital of North Korea.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ec3a148190bb184ba0d481b16a |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f132062b108190ad33656c386ee603 |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 8, 2026, 9:43 p.m.