Triple
T11893514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dérbi Paulista |
E282976
|
entity |
| Predicate | hasRivalryIntensityFactors |
P80734
|
FINISHED |
| Object | historical title disputes |
—
|
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: historical title disputes | Statement: [Dérbi Paulista, hasRivalryIntensityFactors, historical title disputes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRivalryIntensityFactors Context triple: [Dérbi Paulista, hasRivalryIntensityFactors, historical title disputes]
-
A.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
B.
hasRivalryContext
Indicates that there exists a competitive or adversarial relationship between entities within a specific situational or contextual framework.
-
C.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
D.
hasRivalryRoot
chosen
Indicates that a rivalry relationship originates from, or is fundamentally based on, a particular source, cause, or underlying factor.
-
E.
rivalryLevel
Indicates the degree or intensity of competitive opposition or conflict between two entities.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.