Triple
T1328344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Súper Clásico |
E28381
|
entity |
| Predicate | rivalryAspect |
P8277
|
FINISHED |
| Object | sporting success rivalry |
—
|
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: sporting success rivalry | Statement: [El Súper Clásico, rivalryAspect, sporting success rivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rivalryAspect Context triple: [El Súper Clásico, rivalryAspect, sporting success rivalry]
-
A.
hasRivalryAspect
chosen
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
B.
rivalryCharacterization
Indicates a relationship in which two entities are characterized as rivals, typically defined by ongoing competition, opposition, or conflict between them.
-
C.
rivalryName
Indicates that a specific name or label is assigned to a rivalry relationship between two entities.
-
D.
divisionRivalry
Indicates a competitive or adversarial relationship between entities that belong to the same division or subgroup within a larger organization or system.
-
E.
rivalOf
Indicates a relationship in which two entities compete against or oppose each other, often seeking advantage in the same domain or objective.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c1d8188190b15a641a08345adc |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.