Triple
T9745156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region 10 |
E236287
|
entity |
| Predicate | hasProvince |
P285
|
FINISHED |
| Object | Bukidnon |
E236288
|
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: Bukidnon | Statement: [Region 10, hasProvince, Bukidnon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bukidnon Context triple: [Region 10, hasProvince, Bukidnon]
-
A.
Bukidnon
chosen
Bukidnon is a landlocked, mountainous province in the Philippines known for its vast agricultural plantations, cool climate, and scenic highland landscapes.
-
B.
Bontoc
Bontoc is an Austronesian language spoken by the Bontoc people in the Mountain Province of the northern Philippines.
-
C.
Bontoc
Bontoc is a coastal municipality in the province of Southern Leyte in the Philippines known for its agricultural economy and rural communities.
-
D.
Yakan
Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
-
E.
Sugbuanon
Sugbuanon refers to the Cebuano people, a Visayan ethnolinguistic group from the central and southern Philippines known for speaking the Cebuano language.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2f8e648190ad94c940f9dc1de0 |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcd2e08c8190808b58fdabe0c9d3 |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:23 p.m.