Triple
T20001959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayabas |
E494352
|
entity |
| Predicate | nearbyMunicipality |
P4647
|
FINISHED |
| Object | Pagbilao |
—
|
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: Pagbilao | Statement: [Tayabas, nearbyMunicipality, Pagbilao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pagbilao Context triple: [Tayabas, nearbyMunicipality, Pagbilao]
-
A.
Pagbilao
chosen
Pagbilao is a coastal municipality in the province of Quezon, Philippines, known for its power plant, beaches, and mangrove forests.
-
B.
Argao
Argao is a coastal municipality in the southeastern part of Cebu, Philippines, known for its Spanish-era heritage structures and traditional delicacies.
-
C.
Moalboal
Moalboal is a coastal town in the Philippines renowned for its vibrant coral reefs, sardine runs, and popular diving and snorkeling spots.
-
D.
Guihulngan
Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
-
E.
Calasiao
Calasiao is a municipality in the Philippine province of Pangasinan known for its historic churches and famous native rice cakes called "puto Calasiao."
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a222908190b88e1d11cb1b7ee3 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:32 p.m.