Triple
T21412988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubuagan Kalinga |
E528222
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Lubuagan |
—
|
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: Lubuagan | Statement: [Lubuagan Kalinga, spokenIn, Lubuagan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lubuagan Context triple: [Lubuagan Kalinga, spokenIn, Lubuagan]
-
A.
Lubuagan
chosen
Lubuagan is a landlocked, mountainous municipality in the Philippine province of Kalinga known for its rich indigenous culture and history.
-
B.
Lukbán
Lukbán is a Filipino surname most notably associated with Vicente Lukbán, a revolutionary general and leader during the Philippine struggle against Spanish and American colonial rule.
-
C.
Kapangan
Kapangan is a rural municipality in the mountainous province of Benguet in the Philippines, known for its cool climate, highland farms, and scenic Cordillera landscapes.
-
D.
Bucoda
Bucoda is a small town in Thurston County, Washington, known for its historic coal-mining roots and its claim as the "World's Tiniest Town with the Biggest Halloween Spirit."
-
E.
Balamban
Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
- 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_69e0c454c248819093425d1099101c09 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b20017d8819096b1a679edc8943a |
completed | April 22, 2026, 11:33 a.m. |
Created at: April 16, 2026, 5:44 p.m.