Triple
T4504395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Governments of the 1930s in the United Kingdom |
E101296
|
entity |
| Predicate | mainPolicy |
P172
|
FINISHED |
| Object | fiscal retrenchment |
—
|
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: fiscal retrenchment | Statement: [National Governments of the 1930s in the United Kingdom, mainPolicy, fiscal retrenchment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPolicy Context triple: [National Governments of the 1930s in the United Kingdom, mainPolicy, fiscal retrenchment]
-
A.
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.
-
B.
advancedPolicyOf
Indicates that one policy is a more developed, detailed, or progressive version of another policy.
-
C.
implementedPolicy
chosen
Indicates that a particular policy has been put into effect or carried out by an entity.
-
D.
policyName
Indicates the specific name or title assigned to a policy associated with an entity.
-
E.
laterPolicy
Indicates that one policy occurs or becomes effective after another policy in time.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fe17608190ae5dc27052b7c337 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd521671688190bc655d25fa77eba2 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.