Triple
T36489862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paragraph Vector |
E899023
|
entity |
| Predicate | embeddingSpace |
P141097
|
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: [Paragraph Vector, embeddingSpace, continuous vector space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: embeddingSpace Context triple: [Paragraph Vector, embeddingSpace, continuous vector space]
-
A.
embeddingType
Indicates the specific kind or category of embedding representation used to encode an entity or data.
-
B.
mapsLatentSpaceWith
Indicates a relationship where one entity transforms or projects another entity into a latent (hidden or abstract) representational space.
-
C.
targetSpace
chosen
Indicates the space, area, or region toward which an action, movement, or effect is directed.
-
D.
differenceFromStaticEmbeddings
Indicates that something differs in some measurable way from a corresponding representation based on static embeddings.
-
E.
seedSpace
Indicates a relationship where an entity provides or occupies an initial area, context, or capacity from which growth, development, or further allocation can begin.
- F. None of above.
Provenance (3 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. |
Created at: May 3, 2026, 4:10 p.m.