Triple
T18799828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anti-Grain Geometry |
E459730
|
entity |
| Predicate | isDualLicensed |
P73009
|
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: [Anti-Grain Geometry, isDualLicensed, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDualLicensed Context triple: [Anti-Grain Geometry, isDualLicensed, true]
-
A.
dualLicensed
chosen
Indicates that an entity is simultaneously licensed under two distinct licenses or licensing regimes.
-
B.
canBeLicensedUnder
Indicates that something is eligible or suitable to be granted a particular legal license or licensing terms.
-
C.
dualUse
Indicates that something serves both civilian and military (or peaceful and non-peaceful) purposes simultaneously.
-
D.
hasLicensing
Indicates that one entity holds or is granted licensing rights, permissions, or authorization in relation to another entity or resource.
-
E.
basedOnLicense
Indicates that one entity is derived from, uses, or is governed by the terms of another entity’s 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.