Triple
T23372459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GL(n,ℝ) |
E593509
|
entity |
| Predicate | quotientBySL(n,ℝ) |
P93933
|
FINISHED |
| Object | ℝ\{0} via determinant |
—
|
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: ℝ\{0} via determinant | Statement: [GL(n,ℝ), quotientBySL(n,ℝ), ℝ\{0} via determinant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quotientBySL(n,ℝ)
Context triple: [GL(n,ℝ), quotientBySL(n,ℝ), ℝ\{0} via determinant]
-
A.
quotientedBy
Indicates that one structure or set is formed from another by identifying elements according to an equivalence relation or partition, yielding a quotient.
-
B.
isQuotientOf
Indicates that one quantity is the result of dividing another quantity by a specified divisor.
-
C.
quotientIs
Indicates that one entity is the result of dividing another entity by a specified divisor (i.e., it represents the quotient in a division relationship).
-
D.
quotientByLinearEquivalenceGives
chosen
Indicates that forming a quotient under a specified linear equivalence relation produces or yields a particular resulting object or structure.
-
E.
hasQuotient
Indicates that one quantity or entity is the result of dividing another quantity or entity by a specified divisor.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3af45ec8190a32aa4e5f04f6756 |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:32 p.m.