Triple
T13031900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Néel wall |
E326460
|
entity |
| Predicate | isUsedInModelsOf |
P38600
|
FINISHED |
| Object | domain wall motion |
—
|
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: domain wall motion | Statement: [Néel wall, isUsedInModelsOf, domain wall motion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedInModelsOf Context triple: [Néel wall, isUsedInModelsOf, domain wall motion]
-
A.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
B.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
C.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
D.
usedByModel
chosen
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
E.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efe72348190b52fb4068f5fb829 |
completed | April 10, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:54 p.m.