Triple
T11988525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zamboanga del Sur |
E285344
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Dapitan |
E251471
|
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: Dapitan | Statement: [Zamboanga del Sur, hasCity, Dapitan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dapitan Context triple: [Zamboanga del Sur, hasCity, Dapitan]
-
A.
Dapitan
chosen
Dapitan is a historic coastal city in the Zamboanga Peninsula of the Philippines, best known as the place of exile of national hero José Rizal.
-
B.
Dinalungan
Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
-
C.
Tadyawan
Tadyawan is an Austronesian language spoken by the Mangyan people on the island of Mindoro in the Philippines.
-
D.
Pantabangan
Pantabangan is a municipality in the Philippine province of Nueva Ecija known for the Pantabangan Dam and its role in irrigation and hydroelectric power generation.
-
E.
Kabuntalan
Kabuntalan is a municipality in the province of Maguindanao del Norte in the Philippines, known for its location along the Rio Grande de Mindanao and its predominantly Maguindanaon population.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903ae28708190a826bad1624343eb |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f640b9a481908de1b7858e3db52c |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:46 p.m.