Triple
T20649169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawson Doctrine |
E507440
|
entity |
| Predicate | viewsStateRoleAs |
P102849
|
FINISHED |
| Object | setting monetary framework rather than directing markets |
—
|
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: setting monetary framework rather than directing markets | Statement: [Lawson Doctrine, viewsStateRoleAs, setting monetary framework rather than directing markets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewsStateRoleAs Context triple: [Lawson Doctrine, viewsStateRoleAs, setting monetary framework rather than directing markets]
-
A.
viewsAs
chosen
Indicates that one entity perceives, interprets, or regards another entity in a particular way or role.
-
B.
viewsClientAs
Indicates that one entity regards or treats another entity as a client within a service, business, or professional relationship.
-
C.
viewsBehaviorAs
Indicates that one entity interprets, judges, or regards another entity’s behavior in a particular way.
-
D.
viewIs
Indicates that one entity is a visual representation or perspective of another entity.
-
E.
visibilityRole
Indicates the role or level of access an entity has in determining what information or content is visible to others.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af2076b48190b9c8afb4eac65f46 |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.