Triple
T23272043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Government Licence (OGL) |
E588314
|
entity |
| Predicate | licenceVersion |
P151633
|
FINISHED |
| Object | OGL v1.0 |
—
|
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: OGL v1.0 | Statement: [Open Government Licence (OGL), licenceVersion, OGL v1.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenceVersion Context triple: [Open Government Licence (OGL), licenceVersion, OGL v1.0]
-
A.
licenseName
Indicates the specific name or title of the license under which an entity is provided or governed.
-
B.
licenceCode
Indicates that one entity is associated with a specific license identifier or code that governs its permitted use or distribution.
-
C.
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.
-
D.
licenseFocus
Indicates that a license specifically targets, applies to, or is primarily concerned with a particular subject, activity, or scope.
-
E.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
- 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957518f88190bdd88ccc4e295668 |
completed | April 29, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:47 p.m.