Triple
T7784786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhagalpur |
E187213
|
entity |
| Predicate | nearestAirport |
P22550
|
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: [Bhagalpur, nearestAirport, Gaya Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaya Airport Context triple: [Bhagalpur, nearestAirport, 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former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.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.
Sunan Airport
Sunan Airport is the main international airport serving Pyongyang, the capital of North Korea.
-
D.
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.
-
E.
Iki Airport
Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf210f508190b215a0ab95192689 |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5f4fa6c8190a85ba9019c0e5345 |
completed | March 30, 2026, 10:15 p.m. |
Created at: March 30, 2026, 4:23 p.m.