Triple
T15966975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derby du Nord |
E387215
|
entity |
| Predicate | hasParticipantColor |
P103732
|
FINISHED |
| Object | red and gold (RC Lens) |
—
|
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 gold (RC Lens) | Statement: [Derby du Nord, hasParticipantColor, red and gold (RC Lens)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticipantColor Context triple: [Derby du Nord, hasParticipantColor, red and gold (RC Lens)]
-
A.
hasParticipants
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
B.
containsColor
Indicates that one entity includes or exhibits the color specified by another entity.
-
C.
hasParticipantForce
Indicates that an event or action involves a participant specifically in the role of exerting or applying force.
-
D.
hasTeamColorContrast
Indicates that there is a sufficient visual contrast between the colors associated with a team and another relevant color set (such as opponents, background, or interface elements).
-
E.
hasClubColor
chosen
Indicates that a club or team is associated with a specific color or set of colors used to represent it.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.