Triple
T3614428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enlightenment studies |
E76564
|
entity |
| Predicate | examinesImpactOn |
P50422
|
FINISHED |
| Object | modern democracy |
—
|
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: modern democracy | Statement: [Enlightenment studies, examinesImpactOn, modern democracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examinesImpactOn Context triple: [Enlightenment studies, examinesImpactOn, modern democracy]
-
A.
impactOnMarket
Indicates the effect or influence that one factor, event, or action has on market conditions, behavior, or outcomes.
-
B.
impactOnBusiness
Indicates the effect or influence that one factor, event, or action has on a business’s performance, operations, or outcomes.
-
C.
impactOnPerformance
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
-
D.
impactOnHumans
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
E.
hasUpstreamImpactOn
Indicates that one entity’s actions, changes, or outputs affect another entity that is positioned earlier in a process, flow, or dependency chain.
- F. None of above. chosen
Provenance (4 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc279f6948190b9655a4cf3e77d89 |
completed | March 8, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69adb83f1e4c8190ab501c1c05b14c08 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb9bbb62c8190989629ca11733e1b |
completed | March 8, 2026, 6:02 p.m. |
Created at: March 8, 2026, 3:23 p.m.