Triple
T2953756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laffer curve |
E79881
|
entity |
| Predicate | endpointProperty |
P28215
|
FINISHED |
| Object | at 0% tax rate, government revenue is zero |
—
|
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: at 0% tax rate, government revenue is zero | Statement: [Laffer curve, endpointProperty, at 0% tax rate, government revenue is zero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endpointProperty Context triple: [Laffer curve, endpointProperty, at 0% tax rate, government revenue is zero]
-
A.
endPoint
Indicates the terminal location, limit, or final state reached by an object, process, or path in a given relationship or action.
-
B.
endPointExample
Indicates that something serves as a representative or illustrative instance of a particular endpoint.
-
C.
metaProperty
chosen
Indicates that one property functions as a higher-level descriptor or attribute about another property, rather than about an entity directly.
-
D.
hasEndpointCity
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
-
E.
portConfiguration
Indicates how ports are arranged, assigned, or set up for use within a system or device.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98ff874c81908077a90fdc5e8549 |
completed | March 8, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.