Triple
T13031886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Néel wall |
E326460
|
entity |
| Predicate | hasCharacteristicWidth |
P3989
|
FINISHED |
| Object | domain wall width |
—
|
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 width | Statement: [Néel wall, hasCharacteristicWidth, domain wall width]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacteristicWidth Context triple: [Néel wall, hasCharacteristicWidth, domain wall width]
-
A.
hasWidth
chosen
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
B.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
C.
hasStripeWidth
Indicates that one entity possesses stripes characterized by a specified width.
-
D.
hasBorderLengthCharacteristic
Indicates that a border is associated with a specific length-related property or characteristic.
-
E.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
- 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.