Triple
T3199704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Bikol |
E67019
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Bicol Naga |
E336301
|
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: Bicol Naga | Statement: [Central Bikol, hasAlternativeName, Bicol Naga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bicol Naga Context triple: [Central Bikol, hasAlternativeName, Bicol Naga]
-
A.
Bikol Naga
chosen
Bikol Naga is a major dialect of the Central Bikol language spoken in and around Naga City in the Bicol Region of the Philippines.
-
B.
Bukidnon
Bukidnon is a landlocked, mountainous province in the Philippines known for its vast agricultural plantations, cool climate, and scenic highland landscapes.
-
C.
Yakan
Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
-
D.
Ibanag
Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
-
E.
Aguiguan
Aguiguan is a small, uninhabited island in the Northern Mariana Islands known for its rugged terrain and seabird colonies.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9ad4b1c8190bc6ad0f025f238c8 |
completed | March 8, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2621d3bcc8190abf84310bc118757 |
completed | March 12, 2026, 6:50 a.m. |
Created at: March 8, 2026, 3:07 p.m.