Triple
T34964852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Say Never |
E1008363
|
entity |
| Predicate | hasNonlinearElements |
P200961
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Say Never, hasNonlinearElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonlinearElements Context triple: [Say Never, hasNonlinearElements, true]
-
A.
hasNonlinearStructure
chosen
Indicates that the entity possesses a structure whose behavior or relationships among its components are not proportional or additive, i.e., they do not follow a simple linear pattern.
-
B.
isNonlinear
Indicates that the relationship or behavior between variables is not proportional or additive, so it cannot be accurately described by a straight-line (linear) function.
-
C.
hasGeneralNonhomogeneousForm
Indicates that something possesses a general form or structure that is nonhomogeneous, typically meaning it varies across its domain rather than being uniform or constant.
-
D.
typeOfNonlinearity
Indicates the specific kind or form of nonlinearity that characterizes how one entity behaves or responds in relation to another.
-
E.
hasBruteElement
Indicates that an entity possesses or is associated with a raw, force-based, or brute-type elemental property.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a0356f541b08190b40469aa628087f4 |
completed | May 12, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_6a03569e4fa881909c57351a6c489636 |
completed | May 12, 2026, 4:34 p.m. |
Created at: May 3, 2026, 4 p.m.