Triple
T26253916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E8 lattice |
E656669
|
entity |
| Predicate | numberOfMinimalVectors |
P195035
|
FINISHED |
| Object | 240 |
—
|
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: 240 | Statement: [E8 lattice, numberOfMinimalVectors, 240]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMinimalVectors Context triple: [E8 lattice, numberOfMinimalVectors, 240]
-
A.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
-
B.
hasMinimalVectorLength
Indicates that the associated vector has a length (magnitude) that meets or exceeds a specified minimal threshold.
-
C.
dimensionAsVectorSpaceOverℚ
Indicates that the dimension of a given vector space is being considered specifically as a vector space over the field of rational numbers ℚ.
-
D.
vectorLength
Indicates the numerical magnitude or size of a vector, typically computed from its components.
-
E.
hasNumberOfKillingVectors
Indicates the relationship that specifies how many Killing vector fields (symmetries of the metric) a given geometric or physical system possesses.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
| PDg | Predicate description generation | batch_69fd9fef7aac819089cc88dd3d00296d |
completed | May 8, 2026, 8:33 a.m. |
Created at: April 26, 2026, 9:08 p.m.