Triple
T24806211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurwitz quaternions |
E620663
|
entity |
| Predicate | hasRankAsZModule |
P157324
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Hurwitz quaternions, hasRankAsZModule, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankAsZModule Context triple: [Hurwitz quaternions, hasRankAsZModule, 4]
-
A.
canBeOverZModule
Indicates that one entity can be structured or interpreted as a module over the ring of integers ℤ with respect to another entity.
-
B.
canBeTensoredWithZModule
Indicates that an object can form a valid tensor product with a ℤ-module, preserving the required algebraic structure.
-
C.
rankOverℤ
Indicates that one entity has a higher (or superior) rank than another when ranks are compared as integers over the set of all integers ℤ.
-
D.
hasRankVariant
Indicates that one entity is an alternative or variant form of another entity’s rank or hierarchical level.
-
E.
containsRank
Indicates that one entity includes or encompasses another entity that has a specific rank or hierarchical level within it.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f42b11251881908070b93355de64ad |
completed | May 1, 2026, 4:24 a.m. |
Created at: April 18, 2026, 4:50 a.m.