Triple
T2847998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israel Kirzner |
E63025
|
entity |
| Predicate | hasAcademicApproach |
P20107
|
FINISHED |
| Object | subjectivist 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: subjectivist economics | Statement: [Israel Kirzner, hasAcademicApproach, subjectivist economics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicApproach Context triple: [Israel Kirzner, hasAcademicApproach, subjectivist economics]
-
A.
academicApproach
chosen
Indicates an entity’s characteristic method, strategy, or style used in academic work, study, or instruction.
-
B.
hasAcademicStandard
Indicates that an entity is associated with, aligned to, or governed by a specified academic or educational standard.
-
C.
hasAcademicSystem
Indicates that an entity is associated with or operates under a particular academic or educational system.
-
D.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
E.
hasAcademicFunction
Indicates that an entity serves a specific academic role, duty, or function within an educational or scholarly context.
- 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf403698819084fb4ace5839aa05 |
completed | March 7, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69abdd0e86808190bcefffafbd3cd441 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.