Triple
T3428371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diesel (licensed watches) |
E72278
|
entity |
| Predicate | typicalCaseDiameter |
P48665
|
FINISHED |
| Object | oversized relative to standard men’s watches |
—
|
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: oversized relative to standard men’s watches | Statement: [Diesel (licensed watches), typicalCaseDiameter, oversized relative to standard men’s watches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCaseDiameter Context triple: [Diesel (licensed watches), typicalCaseDiameter, oversized relative to standard men’s watches]
-
A.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
B.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
C.
coreStageDiameter
Indicates the diameter measurement of the central or primary stage of an object or system.
-
D.
wheelDiameter
Indicates the size of a wheel measured across its diameter.
-
E.
hasTypicalColumnHeightToDiameterRatio
Indicates that there is a characteristic or commonly observed proportional relationship between a column’s height and its diameter.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb983f4608190abcc27aa7b926deb |
completed | March 8, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69adadfea024819094b41a13bc004bda |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb00f4f8c81908f88daf71f6a9c29 |
completed | March 8, 2026, 5:21 p.m. |
Created at: March 8, 2026, 3:15 p.m.