Triple
T4277149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LogisticRegression |
E97070
|
entity |
| Predicate | usesLinkFunction |
P38257
|
FINISHED |
| Object | logistic |
—
|
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: logistic | Statement: [LogisticRegression, usesLinkFunction, logistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLinkFunction Context triple: [LogisticRegression, usesLinkFunction, logistic]
-
A.
usesFunction
chosen
Indicates that one entity employs, invokes, or relies on a particular function to perform an operation or achieve a result.
-
B.
associatedFunction
Indicates that one entity has a related or linked function that is conceptually or operationally connected to it.
-
C.
usesDirective
Indicates that one entity applies, references, or relies on a specific directive issued or defined by another entity.
-
D.
symbolicallyUses
Indicates that one entity employs another as a symbol or representation to convey meaning, ideas, or associations rather than for its literal or practical function.
-
E.
affectedFunction
Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501ef1388190b0c968b069014a59 |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.