Triple
T28594667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esperanto Wikisource |
E723740
|
entity |
| Predicate | copyrightStatusOfContent |
P7333
|
FINISHED |
| Object | public domain or freely licensed |
—
|
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: public domain or freely licensed | Statement: [Esperanto Wikisource, copyrightStatusOfContent, public domain or freely licensed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: copyrightStatusOfContent Context triple: [Esperanto Wikisource, copyrightStatusOfContent, public domain or freely licensed]
-
A.
copyrightStatus
chosen
Indicates the legal protection state of a work, specifying whether and how it is covered by copyright.
-
B.
copyrightCategory
Indicates the classification of an item according to its copyright status or type of copyright protection.
-
C.
contentLicense
Indicates the type of license or usage rights that govern how the associated content may be used, shared, or redistributed.
-
D.
rightsManagement
Indicates the management, control, and enforcement of usage rights or permissions associated with an entity or resource.
-
E.
contentLicenseAllows
Indicates that a content license grants permission for a specified use or action involving the content.
- 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_69f01d80b1908190980594837604b8c7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 4:21 a.m.