Triple
T4797179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genoa C.F.C. |
E106738
|
entity |
| Predicate | traditionalKit |
P59326
|
FINISHED |
| Object | half red and half blue shirt |
—
|
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: half red and half blue shirt | Statement: [Genoa C.F.C., traditionalKit, half red and half blue shirt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalKit Context triple: [Genoa C.F.C., traditionalKit, half red and half blue shirt]
-
A.
traditionalMaterial
Indicates that something is made from, incorporates, or is characterized by materials associated with long-established or customary practices.
-
B.
traditionalEnd
Indicates that one entity is the customary or historically established conclusion, outcome, or final stage of another entity or process.
-
C.
homeKitTradition
Indicates a tradition or customary practice associated with a home or household setting.
-
D.
traditionalMotif
Indicates that something incorporates, represents, or is characterized by a motif rooted in established cultural or historical traditions.
-
E.
traditionalCrossType
Indicates that one entity is related to another through a conventional or historically established type of cross or crossing relationship.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6b40c29c8190adab3503f8ba0145 |
completed | March 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69bd622f88188190a51d52ccfad3d2dd |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6b3fb598819084a83d2b765a62b0 |
completed | March 20, 2026, 3:43 p.m. |
Created at: March 20, 2026, 1:22 p.m.