Triple
T36489904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PV-DM |
E899024
|
entity |
| Predicate | vectorSpace |
P185596
|
FINISHED |
| Object | continuous vector space |
—
|
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: continuous vector space | Statement: [PV-DM, vectorSpace, continuous vector space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vectorSpace Context triple: [PV-DM, vectorSpace, continuous vector space]
-
A.
isVectorSpaceOver
Indicates that one mathematical structure forms a vector space with respect to another structure serving as its field of scalars.
-
B.
vector
Indicates that one entity is a vector associated with, representing, or characterizing another entity (such as a quantity with magnitude and direction, or a carrier/representative of something).
-
C.
vectorType
Indicates that one entity is classified as the type or category of vector associated with another entity.
-
D.
nullSpace
Indicates that a vector lies in the null space of a linear transformation, meaning it is mapped to the zero vector by that transformation.
-
E.
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.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.