Triple
T33573193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nina Paley |
E859956
|
entity |
| Predicate | licenseUsedForWork |
P130577
|
FINISHED |
| Object | Creative Commons Attribution-ShareAlike |
—
|
NE NERFINISHED |
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: Creative Commons Attribution-ShareAlike | Statement: [Nina Paley, licenseUsedForWork, Creative Commons Attribution-ShareAlike]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseUsedForWork Context triple: [Nina Paley, licenseUsedForWork, Creative Commons Attribution-ShareAlike]
-
A.
licenseUsedInWork
Indicates that a particular license is applied to or governs the use of a specific work.
-
B.
licenseUsed
chosen
Indicates that a particular license has been applied to or is being utilized for a specific resource, activity, or entity.
-
C.
workUsedAs
Indicates that one work is employed or utilized in the creation, performance, or presentation of another work.
-
D.
workUsedFor
Indicates that a particular work (such as a document, artwork, or dataset) is employed or utilized for a specific purpose, task, or function.
-
E.
licensesWorksBy
Indicates that one entity grants legal permission for the use or exploitation of works created by another entity.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f7473bfc8190a283ceb7e4c80474 |
completed | May 3, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.