Triple
T13031887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Néel wall |
E326460
|
entity |
| Predicate | widthDependsOn |
P107544
|
FINISHED |
| Object | exchange stiffness |
—
|
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: exchange stiffness | Statement: [Néel wall, widthDependsOn, exchange stiffness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widthDependsOn Context triple: [Néel wall, widthDependsOn, exchange stiffness]
-
A.
widthInColumns
Indicates the number of column units that an element or item spans within a grid or layout.
-
B.
width
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
C.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
D.
proportionWidth
Indicates that one entity’s width is defined as a proportional (scaled) value relative to another reference width.
-
E.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69d97e3df2288190a7f27d31d248bb7f |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 8:54 p.m.