Triple
T18257358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statistics and Machine Learning Toolbox |
E437249
|
entity |
| Predicate | includesAlgorithm |
P125667
|
FINISHED |
| Object | linear regression |
—
|
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: linear regression | Statement: [Statistics and Machine Learning Toolbox, includesAlgorithm, linear regression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesAlgorithm Context triple: [Statistics and Machine Learning Toolbox, includesAlgorithm, linear regression]
-
A.
relatedAlgorithm
Indicates that one algorithm has a meaningful connection or association with another algorithm, such as similarity, dependency, or complementary function.
-
B.
includesAPI
Indicates that one entity provides or contains an application programming interface (API) that can be used by another entity.
-
C.
hasComponentAlgorithm
chosen
Indicates that an entity includes or is composed of a specific algorithm as one of its constituent components.
-
D.
algorithmType
Indicates the specific kind or category of algorithm associated with an entity or process.
-
E.
includesFinal
Indicates that one entity contains or encompasses another entity as its concluding or last part.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd86e21081909c049082949b95c6 |
completed | April 19, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.