Triple
T27233493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOF (Thailand) |
E682215
|
entity |
| Predicate | hasRevenueFunction |
P112669
|
FINISHED |
| Object | design of tax system |
—
|
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: design of tax system | Statement: [MOF (Thailand), hasRevenueFunction, design of tax system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRevenueFunction Context triple: [MOF (Thailand), hasRevenueFunction, design of tax system]
-
A.
hasRevenueUnit
Indicates that an entity’s revenue is measured, reported, or associated in terms of a specified unit (e.g., currency or measurement unit).
-
B.
hasRevenueSystem
chosen
Indicates that one entity possesses, uses, or is associated with a particular revenue-generating system or mechanism.
-
C.
usesRevenueModel
Indicates that one entity applies or operates according to a particular revenue model to generate income.
-
D.
revenueUse
Indicates how generated revenue is allocated, spent, or applied toward specific purposes or activities.
-
E.
hasSecondaryRevenueModel
Indicates that an entity has an additional, non-primary way of generating revenue beyond its main business model.
- 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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fe87b609888190913b0c3f787ecdba |
completed | May 9, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69fe8731af48819092084f6f74bf052d |
completed | May 9, 2026, 1 a.m. |
Created at: April 27, 2026, 9:47 a.m.