Triple
T2301415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew S. Tanenbaum |
E51739
|
entity |
| Predicate | theoryAdvocated |
P33
|
FINISHED |
| Object | microkernel architecture |
—
|
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: microkernel architecture | Statement: [Andrew S. Tanenbaum, theoryAdvocated, microkernel architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoryAdvocated Context triple: [Andrew S. Tanenbaum, theoryAdvocated, microkernel architecture]
-
A.
advocates
chosen
Indicates that one entity publicly supports, recommends, or argues in favor of another entity or its interests.
-
B.
theorized
Indicates that one entity has proposed or developed a theoretical explanation or hypothesis about another entity or phenomenon.
-
C.
advocatesAgainst
Indicates that one entity actively opposes, argues against, or campaigns to prevent or stop another entity, action, or idea.
-
D.
supportsTheory
Indicates that one entity provides evidence, justification, or endorsement for the validity or acceptance of another entity’s theory.
-
E.
appliesTheory
Indicates that an entity uses or implements a particular theory in analyzing, explaining, or addressing something.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcbabf01081908db3b42bc7c60444 |
completed | March 7, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_69abc58ad33c8190b8d68af41b6f5e07 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.