Triple
T1636449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RHT |
E35368
|
entity |
| Predicate | associatedWithLicenseModel |
P2830
|
FINISHED |
| Object | open-source licenses |
—
|
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-source licenses | Statement: [RHT, associatedWithLicenseModel, open-source licenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLicenseModel Context triple: [RHT, associatedWithLicenseModel, open-source licenses]
-
A.
licenseModel
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
B.
supportsLicense
Indicates that one entity is compatible with, enables, or is configured to work under a specified license.
-
C.
hasLicense
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
D.
associatedWithUnit
Indicates that one entity has a connection, linkage, or affiliation with a particular unit (such as a division, department, or organizational subunit).
-
E.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907cac610819083cafd4396b6d66c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.