Triple
T7727095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gibson F-5 style mandolin |
E175156
|
entity |
| Predicate | hasNutWidth |
P3989
|
FINISHED |
| Object | approximately 1 1/8 inches (typical) |
—
|
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: approximately 1 1/8 inches (typical) | Statement: [Gibson F-5 style mandolin, hasNutWidth, approximately 1 1/8 inches (typical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNutWidth Context triple: [Gibson F-5 style mandolin, hasNutWidth, approximately 1 1/8 inches (typical)]
-
A.
usesNutType
Indicates that one entity employs or incorporates a specific type of nut in its structure, function, or composition.
-
B.
hasWidth
chosen
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
C.
isNarrowestPartOf
Indicates that one entity constitutes the slimmest or most constricted section within the extent or structure of another entity.
-
D.
isNarrow
Indicates that something has a small width or limited breadth relative to a reference or context.
-
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.
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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:06 p.m.