Triple
T26967167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CNT |
E679201
|
entity |
| Predicate | jerseyAffiliation |
P16782
|
FINISHED |
| Object | United States national colors |
—
|
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: United States national colors | Statement: [CNT, jerseyAffiliation, United States national colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyAffiliation Context triple: [CNT, jerseyAffiliation, United States national colors]
-
A.
jerseyHonor
Indicates that an entity has been honored by having its jersey formally recognized, typically through retirement or special commemoration.
-
B.
jersey
Indicates that one entity is the jersey (sports uniform top) associated with, worn by, or representing another entity.
-
C.
jerseySport
Indicates that a particular jersey is associated with or used in a specific sport.
-
D.
jerseyName
Indicates the name or label that appears on an entity’s jersey or uniform.
-
E.
jerseySignificance
chosen
Indicates the importance, meaning, or symbolic value associated with a particular jersey in a given context.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 6:36 a.m.