Triple
T15799736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subic Bay Metropolitan Authority |
E383065
|
entity |
| Predicate | grantsIncentives |
P79344
|
FINISHED |
| Object | tax incentives to locators |
—
|
LITERAL 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: tax incentives to locators | Statement: [Subic Bay Metropolitan Authority, grantsIncentives, tax incentives to locators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantsIncentives Context triple: [Subic Bay Metropolitan Authority, grantsIncentives, tax incentives to locators]
-
A.
providesIncentivesTo
chosen
Indicates that one entity offers rewards, benefits, or motivations to another entity to encourage a desired behavior or outcome.
-
B.
stateIncentives
Indicates that a state government provides benefits, subsidies, or other inducements to encourage a particular action, behavior, or investment.
-
C.
providedTaxIncentivesForSavings
Indicates that an authority or organization granted tax benefits to encourage individuals or entities to save money.
-
D.
grantProgram
Indicates that an entity administers or is associated with a structured grant-based funding program.
-
E.
relatedGrantScheme
Indicates that there is an associated grant scheme that is relevant or linked to the subject entity.
- F. None of above.
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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e135b08190b736e77bac5e2bff |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.