Triple
T11740985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panay |
E279151
|
entity |
| Predicate | neighboringIsland |
P19482
|
FINISHED |
| Object | Masbate |
E267334
|
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: Masbate | Statement: [Panay, neighboringIsland, Masbate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masbate Context triple: [Panay, neighboringIsland, Masbate]
-
A.
Masbate
chosen
Masbate is an island province in the central Philippines, known for its cattle ranches, rodeo festivals, and location between Luzon and the Visayas.
-
B.
Masbateño
Masbateño is a Central Philippine Bisayan language spoken primarily on Masbate Island in the Philippines.
-
C.
Malabago
Malabago is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
-
D.
Chamorga
Chamorga is a small, remote village on the northeastern tip of Tenerife in the Canary Islands, known for its traditional rural character and scenic hiking routes through the surrounding mountains and coastline.
-
E.
Malabuyoc
Malabuyoc is a coastal municipality in the southwestern part of Cebu province in the Philippines, known for its hot springs and scenic seaside landscapes.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f025f88190a39280806c9d7c33 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0901a6ed481909054ddd581935ac4 |
completed | April 28, 2026, 10:46 a.m. |
Created at: April 8, 2026, 9:41 p.m.