Triple
T13236453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Laffer |
E315157
|
entity |
| Predicate | theoryAssociatedWith |
P2830
|
FINISHED |
| Object | trickle-down economics |
—
|
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: trickle-down economics | Statement: [Arthur Laffer, theoryAssociatedWith, trickle-down economics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoryAssociatedWith Context triple: [Arthur Laffer, theoryAssociatedWith, trickle-down economics]
-
A.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
B.
relatedTheorem
Indicates that one theorem is connected to another through a logical, thematic, or derivational relationship.
-
C.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
D.
theoryType
Indicates the classification relationship that specifies what type or category of theory an entity belongs to.
-
E.
architectureAssociated
Indicates that there is a relationship or connection between an entity and a particular architectural style, feature, or practice.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d56da008190af55da3a9e7ffd4d |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:22 p.m.