Triple
T13088006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bataan |
E310386
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Dinalupihan |
E335735
|
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: Dinalupihan | Statement: [Bataan, hasMunicipality, Dinalupihan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dinalupihan Context triple: [Bataan, hasMunicipality, Dinalupihan]
-
A.
Dinalupihan
chosen
Dinalupihan is a landlocked municipality in the province of Bataan in the Philippines, known for its agricultural economy and strategic location as a gateway between Central Luzon and the Bataan Peninsula.
-
B.
Nabunturan
Nabunturan is a landlocked municipality in the Philippines known as the administrative and commercial center of the province of Davao de Oro on Mindanao island.
-
C.
Kidapawan
Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
-
D.
Dipaculao
Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
-
E.
Bansalan
Bansalan is a municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and rural communities.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981378dd08190b4f00e4e5df0e480 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73053a1888190a234e8c119a4202a |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:02 p.m.