Triple
T414850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Keynesian economics |
E9569
|
entity |
| Predicate | hasTheoreticalBasisIn |
P7125
|
FINISHED |
| Object | microfoundations |
—
|
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: microfoundations | Statement: [New Keynesian economics, hasTheoreticalBasisIn, microfoundations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTheoreticalBasisIn Context triple: [New Keynesian economics, hasTheoreticalBasisIn, microfoundations]
-
A.
occursInTheory
Indicates that an event, concept, or phenomenon is situated, described, or analyzed within a particular theoretical framework or theory.
-
B.
isBasedOn
chosen
Indicates that one entity is derived from, inspired by, or developed using the content, structure, or principles of another entity.
-
C.
appliesTheory
Indicates that an entity uses or implements a particular theory in analyzing, explaining, or addressing something.
-
D.
supportsTheory
Indicates that one entity provides evidence, justification, or endorsement for the validity or acceptance of another entity’s theory.
-
E.
theorized
Indicates that one entity has proposed or developed a theoretical explanation or hypothesis about another entity or phenomenon.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edcff4688190809d83d112ff25a5 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.