Triple
T8106282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boca |
E189233
|
entity |
| Predicate | hasHistoricRivalryType |
P22384
|
FINISHED |
| Object | city rivalry with River Plate |
—
|
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 rivalry with River Plate | Statement: [Boca, hasHistoricRivalryType, city rivalry with River Plate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricRivalryType Context triple: [Boca, hasHistoricRivalryType, city rivalry with River Plate]
-
A.
hasHistoricRivalry
chosen
Indicates a long-standing, often competitive or adversarial relationship between two entities, typically rooted in significant past conflicts or repeated opposition.
-
B.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
C.
hasRivalryContext
Indicates that there exists a competitive or adversarial relationship between entities within a specific situational or contextual framework.
-
D.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
E.
hasHistoricalTieTo
Indicates a relationship where one entity is historically connected or linked to another through past events, associations, or influences.
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42f735c8819090d0d822644c0a51 |
completed | March 31, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69cb04a2ed1c8190b73562321ad688bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:31 p.m.