Triple
T16397233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabangan |
E398213
|
entity |
| Predicate | sharesProvinceWith |
P102605
|
FINISHED |
| Object | Botolan |
E398205
|
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: Botolan | Statement: [Cabangan, sharesProvinceWith, Botolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Botolan Context triple: [Cabangan, sharesProvinceWith, Botolan]
-
A.
Botolan
chosen
Botolan is a coastal municipality in the province of Zambales in the Philippines, known for its Aeta communities, beaches, and proximity to Mount Pinatubo.
-
B.
Boll
Boll is a district or locality within the town of Oberndorf am Neckar in the German state of Baden-Württemberg.
-
C.
Bott
Bott is a surname most prominently associated with Raoul Bott, a Hungarian-American mathematician known for his influential work in topology and geometry.
-
D.
Botlek
Botlek is an industrial and petrochemical port area within the Port of Rotterdam, known for its large-scale chemical plants, storage terminals, and logistics facilities.
-
E.
Bola
Bola is the given name of Bola Tinubu, a prominent Nigerian politician and current president of Nigeria.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327cb3c708190b64341cb1410ed81 |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00357838a88190be88c51f454be6eb |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:09 a.m.