Triple
T736627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minkowski sum |
E14947
|
entity |
| Predicate | hasIdentityElement |
P19411
|
FINISHED |
| Object | set containing only the zero vector |
—
|
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: set containing only the zero vector | Statement: [Minkowski sum, hasIdentityElement, set containing only the zero vector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIdentityElement Context triple: [Minkowski sum, hasIdentityElement, set containing only the zero vector]
-
A.
hasIdentity
Indicates that one entity is the same as, or is identified as, another specific entity or identifier.
-
B.
isHomogeneous
Indicates that all elements or parts involved share the same type, nature, or characteristics, without significant variation among them.
-
C.
usesSymmetryGroup
Indicates that one entity employs or is based on a particular symmetry group in its structure, behavior, or formulation.
-
D.
hasIsometryGroup
Indicates that one entity possesses or is associated with a particular isometry group describing all distance-preserving transformations of that entity.
-
E.
hasIdentityDocument
Indicates that an entity possesses or is associated with a specific identity document.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a64957ec81909fe2e2dbffd80ed3 |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.