Triple
T13183051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilar, Bataan |
E313776
|
entity |
| Predicate | provinceCapital |
P16248
|
FINISHED |
| Object | Balanga |
E254766
|
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: Balanga | Statement: [Pilar, Bataan, provinceCapital, Balanga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Balanga Context triple: [Pilar, Bataan, provinceCapital, Balanga]
-
A.
Balanga
chosen
Balanga is a coastal city in the province of Bataan in the Philippines, situated along the shores of Manila Bay.
-
B.
Lubuagan
Lubuagan is a landlocked, mountainous municipality in the Philippine province of Kalinga known for its rich indigenous culture and history.
-
C.
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."
-
D.
Bayambang
Bayambang is a municipality in the province of Pangasinan in the Philippines, known for its agricultural economy and historical significance dating back to the Spanish colonial period.
-
E.
Cauayan
Cauayan is a rapidly developing component city located in the province of Isabela in the Cagayan Valley 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c4a0b0081908027bf77442ff5ff |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78acdaae881908825e5308f0ba388 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:15 p.m.