Triple
T11197666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derbi barceloní |
E264962
|
entity |
| Predicate | hasDerbyType |
P81009
|
FINISHED |
| Object | city derby |
—
|
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: city derby | Statement: [Derbi barceloní, hasDerbyType, city derby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDerbyType Context triple: [Derbi barceloní, hasDerbyType, city derby]
-
A.
typeOfDerby
chosen
Indicates that one entity is a specific kind or category of derby in relation to another entity.
-
B.
hasDerbyStatus
Indicates that an entity holds a specific status or classification related to a derby event or competition.
-
C.
hasDerbyColor
Indicates that one entity (typically a derby or race event) is associated with a specific color used to represent or identify it.
-
D.
derbyInvolves
Indicates that a particular derby event includes or features the participation of a specified entity or entities.
-
E.
derby
Indicates a competitive match or contest, typically between closely linked or rival entities (such as teams from the same area or group).
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8c082fc8190866c574f698b59ef |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:29 p.m.