Triple
T2264234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Negros Oriental |
E50107
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object | Sibulan Airport |
E235325
|
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: Sibulan Airport | Statement: [Negros Oriental, hasAirport, Sibulan Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sibulan Airport Context triple: [Negros Oriental, hasAirport, Sibulan Airport]
-
A.
Sibulan Airport
chosen
Sibulan Airport is a domestic airport serving Dumaguete and the surrounding areas in Negros Oriental, in the Central Visayas region of the Philippines.
-
B.
Dumna Airport
Dumna Airport is a domestic airport serving the city of Jabalpur in the Indian state of Madhya Pradesh.
-
C.
Puyo Airport
Puyo Airport is a regional public airport serving the city of Puyo and the surrounding area in Ecuador’s Amazonian Pastaza Province.
-
D.
Tambolaka Airport
Tambolaka Airport is a regional airport serving the western part of Sumba Island in East Nusa Tenggara, Indonesia, providing domestic connections to major Indonesian cities.
-
E.
Siquijor Airport
Siquijor Airport is a small domestic airport serving the island province of Siquijor in the Central Visayas region of the Philippines.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18d7fc08190851765683d1b8092 |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71cfd3b08190988474aa0fa985fe |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.