Triple
T10546579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Asawa Estate |
E248832
|
entity |
| Predicate | overseesLicensingOf |
P38010
|
FINISHED |
| Object | Ruth Asawa images |
—
|
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: Ruth Asawa images | Statement: [Ruth Asawa Estate, overseesLicensingOf, Ruth Asawa images]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overseesLicensingOf Context triple: [Ruth Asawa Estate, overseesLicensingOf, Ruth Asawa images]
-
A.
hasLicensing
Indicates that one entity holds or is granted licensing rights, permissions, or authorization in relation to another entity or resource.
-
B.
licenseStewardship
chosen
Indicates that one entity is responsible for managing, overseeing, or administering a license on behalf of another entity.
-
C.
licensingComponent
Indicates that one entity serves as a licensing-related component or module within the context or operation of another entity.
-
D.
licenseFor
Indicates that one entity grants or holds formal permission or authorization for another entity to perform an activity, use a resource, or operate under specified conditions.
-
E.
positionOnLicensing
Indicates the stance, policy, or viewpoint an entity holds regarding licensing terms, rights, or practices.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52710869c81909b6db1a190825bad |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:33 p.m.