Triple
T384153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Moderation |
E8742
|
entity |
| Predicate | hasProposedCause |
P10735
|
FINISHED |
| Object | improved monetary policy |
—
|
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: improved monetary policy | Statement: [Great Moderation, hasProposedCause, improved monetary policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProposedCause Context triple: [Great Moderation, hasProposedCause, improved monetary policy]
-
A.
hasCause
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
B.
hasProposedResolutionType
Indicates the type or category of resolution that has been formally proposed in relation to an issue, dispute, or decision.
-
C.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
-
E.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec422b808190b6ddf747ef939151 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e967d84c8190a6b647f78d95d4e4 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.