Triple
T15524014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adidas Terrestra Silverstream |
E369036
|
entity |
| Predicate | circumferenceClass |
P89169
|
FINISHED |
| Object | FIFA-regulation match ball circumference |
—
|
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: FIFA-regulation match ball circumference | Statement: [Adidas Terrestra Silverstream, circumferenceClass, FIFA-regulation match ball circumference]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circumferenceClass Context triple: [Adidas Terrestra Silverstream, circumferenceClass, FIFA-regulation match ball circumference]
-
A.
circumference
Indicates the total length around the boundary of a closed curve, typically a circle, relating a shape to the measure of its perimeter.
-
B.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
C.
baseCircumference
Indicates the circumference measurement of the base of an object or geometric figure.
-
D.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
-
E.
ballCircumferenceRange
chosen
Indicates the range of possible circumferences that a ball can have.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04143bda08190a2dee44918c1ad1c |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:05 a.m.