Triple
T179444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janet–Cartan theorem |
E3651
|
entity |
| Predicate | dimensionBoundType |
P7032
|
FINISHED |
| Object | local embedding dimension upper bound |
—
|
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: local embedding dimension upper bound | Statement: [Janet–Cartan theorem, dimensionBoundType, local embedding dimension upper bound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionBoundType Context triple: [Janet–Cartan theorem, dimensionBoundType, local embedding dimension upper bound]
-
A.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
B.
hasBoundaryType
Indicates that one entity has a boundary characterized by a specific type or classification in relation to another entity or context.
-
C.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
D.
demarcationType
Indicates the specific way in which a boundary or separation between entities is defined, marked, or categorized.
-
E.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.