Triple
T22668757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevalley groups |
E559863
|
entity |
| Predicate | haveSubtype |
P21666
|
FINISHED |
| Object | split simple algebraic groups |
—
|
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: split simple algebraic groups | Statement: [Chevalley groups, haveSubtype, split simple algebraic groups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveSubtype Context triple: [Chevalley groups, haveSubtype, split simple algebraic groups]
-
A.
hasSubproperty
Indicates that one property is a more specific version of another property, inheriting its meaning and constraints.
-
B.
hadSubtypes
Indicates that an entity served as a broader category or type that included one or more more specific subtypes.
-
C.
hasSubConcept
chosen
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
-
D.
hasMultipleSubclasses
Indicates that a class or category is related to more than one distinct subclass within a hierarchy.
-
E.
hasSubset
Indicates that one set is entirely contained within another set, with all elements of the first set also belonging to the second.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781de1d48190947cb1bb9d0890d9 |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:09 p.m.