Triple
T6474969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Luzon |
E146048
|
entity |
| Predicate | includesProvince |
P11085
|
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: [Southern Luzon, includesProvince, Masbate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masbate Context triple: [Southern Luzon, includesProvince, 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.
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.
-
D.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
E.
Malabanias
Malabanias is a barangay (village-level administrative district) within Angeles City in Pampanga, Philippines, known for its mixed residential, commercial, and entertainment areas.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a341360819082f2b5496a1a68b0 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fd1db288190b00ba6d7f3aae925 |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:50 p.m.