Triple
T34956066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bram Moolenaar |
E1008124
|
entity |
| Predicate | licenseModelPromoted |
P182122
|
FINISHED |
| Object | open source |
—
|
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 | Statement: [Bram Moolenaar, licenseModelPromoted, open source]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseModelPromoted Context triple: [Bram Moolenaar, licenseModelPromoted, open source]
-
A.
licenseModel
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
B.
licenseFor
Indicates that one entity grants or holds formal permission or authorization for another entity to perform an activity, use a resource, or operate under specified conditions.
-
C.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
-
D.
licenseTier
Indicates the specific level or category of licensing assigned to an entity within a tiered licensing structure.
-
E.
licenseUsed
Indicates that a particular license has been applied to or is being utilized for a specific resource, activity, or entity.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.