Triple
T21934745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodrik trilemma |
E541658
|
entity |
| Predicate | analyticalLevel |
P11425
|
FINISHED |
| Object | macro-level |
—
|
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: macro-level | Statement: [Rodrik trilemma, analyticalLevel, macro-level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analyticalLevel Context triple: [Rodrik trilemma, analyticalLevel, macro-level]
-
A.
logicalLevel
chosen
Indicates the relative position or depth of something within a hierarchy of abstraction, reasoning, or logical structure.
-
B.
assessmentLevel
Indicates the degree, rating, or intensity assigned to an evaluation or judgment of something.
-
C.
statisticalLevel
Indicates the degree or tier of statistical detail, aggregation, or granularity at which data or analysis is defined or reported.
-
D.
classificationLevel
Indicates the degree or tier within an ordered system or hierarchy to which something is assigned for categorization or control purposes.
-
E.
measurementLevel
Indicates the degree or scale at which something is measured or quantified, such as its level, intensity, or magnitude.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12402f7ac81909b14586a46d971bb |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:51 p.m.