Triple
T30085001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitchin cycles |
E764578
|
entity |
| Predicate | scaleOfImpact |
P97046
|
FINISHED |
| Object | minor compared to major business cycles |
—
|
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: minor compared to major business cycles | Statement: [Kitchin cycles, scaleOfImpact, minor compared to major business cycles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scaleOfImpact Context triple: [Kitchin cycles, scaleOfImpact, minor compared to major business cycles]
-
A.
hasImpactScale
chosen
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
-
B.
impactLevel
Indicates the degree or intensity of effect that one entity, action, or event has on another.
-
C.
impactScope
Indicates the extent or range within which an action, event, or entity produces effects or consequences.
-
D.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
E.
timeHorizonOfImpact
Indicates the span of time over which an action, event, or factor is expected to produce its effects or consequences.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d6b85488190a14499b6bb2c9241 |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:04 p.m.