Triple
T2847989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israel Kirzner |
E63025
|
entity |
| Predicate | theoryFocus |
P31
|
FINISHED |
| Object | role of entrepreneurship in market coordination |
—
|
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: role of entrepreneurship in market coordination | Statement: [Israel Kirzner, theoryFocus, role of entrepreneurship in market coordination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoryFocus Context triple: [Israel Kirzner, theoryFocus, role of entrepreneurship in market coordination]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
C.
formerFocus
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
-
D.
programFocus
Indicates that an educational or training program is primarily oriented around or concentrated on a particular subject, theme, or objective.
-
E.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
- 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.