Triple
T5743880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibuyan Sea |
E126680
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Romblon |
E192440
|
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: Romblon | Statement: [Sibuyan Sea, borderedBy, Romblon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romblon Context triple: [Sibuyan Sea, borderedBy, Romblon]
-
A.
Romblon
chosen
Romblon is an island province in the Philippines known for its marble industry, clear waters, and scenic beaches.
-
B.
Dinagat Islands
Dinagat Islands is a province in the Caraga region of the Philippines known for its rugged coastline, rich marine biodiversity, and relatively remote, less-developed island communities.
-
C.
Marinduque
Marinduque is an island province in the Philippines known for its heart-shaped geography and the annual Moriones Festival.
-
D.
Tawi-Tawi
Tawi-Tawi is the Philippines’ southernmost island province, known for its predominantly Muslim population, rich maritime culture, and proximity to Malaysia and Indonesia.
-
E.
Siquijor
Siquijor is a small island province in the central Philippines known for its white-sand beaches, coral reefs, and folklore surrounding mysticism and traditional healing.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02586b25c819083c409ce324268cc |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e27ba848190b0c289a804b865cd |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.