Triple
T12562354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisualWorks |
E295379
|
entity |
| Predicate | hasCommercialLicensing |
P70564
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [VisualWorks, hasCommercialLicensing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialLicensing Context triple: [VisualWorks, hasCommercialLicensing, true]
-
A.
hasLicensing
chosen
Indicates that one entity holds or is granted licensing rights, permissions, or authorization in relation to another entity or resource.
-
B.
usesLicensingModel
Indicates that one entity employs or applies a particular licensing model in its operations or offerings.
-
C.
isNonCommercial
Indicates that the associated entity, use, or activity is not intended for or involved in commercial, profit-generating purposes.
-
D.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
E.
licensingRestriction
Indicates that there is a constraint or condition imposed on the use, distribution, or modification of something under a specific license.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 11:48 p.m.