Triple
T1717931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RISC-V |
E37329
|
entity |
| Predicate | hasLicenseModel |
P8460
|
FINISHED |
| Object | open and non-restrictive license |
—
|
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: open and non-restrictive license | Statement: [RISC-V, hasLicenseModel, open and non-restrictive license]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLicenseModel Context triple: [RISC-V, hasLicenseModel, open and non-restrictive license]
-
A.
hasLicense
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
B.
licenseModel
chosen
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
C.
supportsLicense
Indicates that one entity is compatible with, enables, or is configured to work under a specified license.
-
D.
engineLicenseBasedOn
Indicates that an engine’s license is determined or derived from another specified license or licensing basis.
-
E.
licenseManufacturerOf
Indicates that one entity is authorized, via a license, to manufacture products or goods on behalf of or under the rights of 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab5c96db6c8190a745d6fef7bf2cdb |
completed | March 6, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69aa61bed2fc819086d912cd34285978 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.