Triple
T5425658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E(n) |
E121355
|
entity |
| Predicate | hasLieAlgebraDimension |
P63682
|
FINISHED |
| Object | n(n+1)/2 |
—
|
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: n(n+1)/2 | Statement: [E(n), hasLieAlgebraDimension, n(n+1)/2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLieAlgebraDimension Context triple: [E(n), hasLieAlgebraDimension, n(n+1)/2]
-
A.
hasLieAlgebra
Indicates that one mathematical structure is associated with, or gives rise to, a specific Lie algebra capturing its infinitesimal or tangent-level structure.
-
B.
hasDimensionality
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
C.
hasKrullDimension
Indicates that a mathematical structure (typically a ring or scheme) is associated with a specific Krull dimension, measuring the maximal length of chains of its prime ideals.
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
isNonAbelian
Indicates that the operation or structure in question does not satisfy commutativity, so the order of applying the operation matters.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8910de688190aa0cd80627849a60 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:06 p.m.