Triple
T36489833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paragraph Vector |
E899023
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | document embedding method |
C15494
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: document embedding method Context triple: [Paragraph Vector, instanceOf, document embedding method]
-
A.
documentation corpus
A documentation corpus is a structured collection of written materials, such as manuals, guides, and reference texts, compiled to provide comprehensive information and support for a specific domain, product, or system.
-
B.
partition-based clustering method
A partition-based clustering method is an approach that divides a dataset into a predefined number of non-overlapping groups (clusters) by directly assigning each data point to exactly one cluster based on a chosen similarity or distance measure.
-
C.
unsupervised learning method
chosen
An unsupervised learning method is a type of machine learning approach that discovers patterns, structures, or groupings in unlabeled data without predefined output targets.
-
D.
metadata annotation mechanism
A metadata annotation mechanism is a system or feature that allows attaching structured, descriptive information to data, code, or resources to enable enhanced interpretation, processing, and tooling support.
-
E.
content-addressable memory system
A content-addressable memory system is a storage architecture that retrieves data based on its content or pattern rather than its specific memory address.
- F. None of above.
Provenance (1 batch)
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. |
Created at: May 3, 2026, 4:10 p.m.