Triple
T99724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volcker shock |
E2014
|
entity |
| Predicate | policyStance |
P4795
|
FINISHED |
| Object | tight 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: tight monetary policy | Statement: [Volcker shock, policyStance, tight monetary policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyStance Context triple: [Volcker shock, policyStance, tight monetary policy]
-
A.
politicalRationale
Indicates the reasoning, justification, or strategic considerations underlying a political decision, stance, or action.
-
B.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
C.
policyTool
Indicates that an entity is a tool, mechanism, or instrument used to design, implement, or enforce a policy.
-
D.
policyFocus
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
E.
governingPolicy
Indicates that one entity serves as the authoritative policy or set of rules that directs, constrains, or regulates the behavior, operation, or decisions of 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a253b95d4c81909d1f2bc37e799c44 |
completed | Feb. 28, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69a24ebfc5a88190bdd1653b9fa541fe |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a253b869448190bd75a3542806b36c |
completed | Feb. 28, 2026, 2:32 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.