Triple
T22098995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laguindingan Airport |
E546116
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Tagoloan |
—
|
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: Tagoloan | Statement: [Laguindingan Airport, cityServed, Tagoloan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tagoloan Context triple: [Laguindingan Airport, cityServed, Tagoloan]
-
A.
Tagoloan
chosen
Tagoloan is a coastal municipality in Misamis Oriental, Philippines, known for its strategic location near Cagayan de Oro and its growing industrial and port activities.
-
B.
Malibcong
Malibcong is a remote, mountainous municipality in the Philippine province of Abra known for its indigenous communities and largely undeveloped natural landscapes.
-
C.
Balamban
Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
-
D.
Sarangani
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
-
E.
Karagawan
Karagawan is a regional dialect of the Isnag language spoken by the Isnag people of northern Luzon in the Philippines.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129131b4c8190b443bc820d9b5c61 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.