Triple
T10170792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibulan Airport |
E235325
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Sibulan |
E253492
|
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 | Statement: [Sibulan Airport, locatedIn, Sibulan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sibulan Context triple: [Sibulan Airport, locatedIn, Sibulan]
-
A.
Sibulan
chosen
Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
-
B.
Guinsiliban
Guinsiliban is a coastal municipality on the island-province of Camiguin in the Philippines, known for its rural communities and proximity to volcanic landscapes and marine attractions.
-
C.
Sibunag
Sibunag is a coastal municipality located on the island province of Guimaras in the Western Visayas region of the Philippines.
-
D.
Binongko
Binongko is an island in Indonesia’s Wakatobi archipelago, known for its traditional blacksmithing culture and remote, rugged coastal landscapes.
-
E.
Sarangani
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9d36608190be78665cc3410cf2 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300f7aafc8190be874efc755bd188 |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:10 p.m.