Triple
T3212762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bicol Region |
E67318
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Masbateño |
E138031
|
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: Masbateño | Statement: [Bicol Region, language, Masbateño]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masbateño Context triple: [Bicol Region, language, Masbateño]
-
A.
Masbateño
chosen
Masbateño is a Central Philippine Bisayan language spoken primarily on Masbate Island in the Philippines.
-
B.
Masbate
Masbate is an island province in the central Philippines, known for its cattle ranches, rodeo festivals, and location between Luzon and the Visayas.
-
C.
Malpaso
Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
-
D.
Mariquina
Mariquina is a commune and town in southern Chile, located in the Los Ríos Region and known for its rural landscapes and Mapuche cultural presence.
-
E.
Mazunte
Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaabba8e481909118d9f888ddcd63 |
completed | March 8, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2771204e0819086ae2838a368589a |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:07 p.m.