Triple
T1235898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlético de Madrid |
E26546
|
entity |
| Predicate | kitHomePattern |
P5928
|
FINISHED |
| Object | red and white striped shirts |
—
|
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: red and white striped shirts | Statement: [Atlético de Madrid, kitHomePattern, red and white striped shirts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kitHomePattern Context triple: [Atlético de Madrid, kitHomePattern, red and white striped shirts]
-
A.
kitPattern
chosen
Indicates the design or visual pattern featured on a team's kit or uniform.
-
B.
traditionalHomeKitPattern
Indicates that an entity follows a conventional or historically established pattern or style associated with traditional home kits or household arrangements.
-
C.
homeKitPattern
Indicates a recurring configuration or usage pattern associated with Apple HomeKit setups or automations.
-
D.
locationPattern
Indicates a recurring or structured spatial relationship, where an entity consistently appears or is arranged in a particular type of location or spatial configuration.
-
E.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf17e0bc8190a066561e6b629fc0 |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.