Triple
T4278979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Widenius |
E97105
|
entity |
| Predicate | licenseConcern |
P55175
|
FINISHED |
| Object | proprietary control over MySQL |
—
|
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: proprietary control over MySQL | Statement: [Michael Widenius, licenseConcern, proprietary control over MySQL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseConcern Context triple: [Michael Widenius, licenseConcern, proprietary control over MySQL]
-
A.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
B.
licenseStatus
Indicates the current state or condition of a license in relation to its validity, permissions, or compliance.
-
C.
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.
-
D.
licensePreference
Indicates a party’s chosen or prioritized type of license to use, grant, or operate under in a given context.
-
E.
licenseScope
Indicates the specific rights, limitations, and conditions that define how and where a license may be used or applied.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350201ac88190b9d8980da5f0d03d |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:07 p.m.