Triple
T28643670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Wikibooks |
E724995
|
entity |
| Predicate | licenseCharacteristic |
P168631
|
FINISHED |
| Object | copyleft |
—
|
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: copyleft | Statement: [Japanese Wikibooks, licenseCharacteristic, copyleft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseCharacteristic Context triple: [Japanese Wikibooks, licenseCharacteristic, copyleft]
-
A.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
B.
licenseFocus
Indicates that a license specifically targets, applies to, or is primarily concerned with a particular subject, activity, or scope.
-
C.
licensePreference
Indicates a party’s chosen or prioritized type of license to use, grant, or operate under in a given context.
-
D.
licenseOptions
Indicates the available licensing choices or configurations that can be applied to an entity or resource.
-
E.
licenceBuiltIn
Indicates that a licence is inherently included within or comes pre-installed as part of another product, system, or component rather than being added separately.
- F. None of above. chosen
Provenance (4 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 28, 2026, 4:46 a.m.