Triple
T30197515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABC Futebol Clube |
E767675
|
entity |
| Predicate | cityRivalryType |
P29010
|
FINISHED |
| Object | Natal derby |
—
|
NE NERFINISHED |
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: Natal derby | Statement: [ABC Futebol Clube, cityRivalryType, Natal derby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityRivalryType Context triple: [ABC Futebol Clube, cityRivalryType, Natal derby]
-
A.
cityRivalry
Indicates a competitive or adversarial relationship that exists between two cities, often involving sports, economics, culture, or historical tensions.
-
B.
rivalryInvolvesCity
Indicates that a rivalry relationship includes or is associated with a particular city as one of its involved locations.
-
C.
rivalryBasis
Indicates the underlying reason, cause, or grounds on which a rivalry between entities is based.
-
D.
rivalryCharacterizedBy
Indicates a relationship where a rivalry is defined or distinguished by a particular feature, quality, or circumstance.
-
E.
typeOfRivalry
chosen
Indicates a competitive or adversarial relationship between entities, specifying the particular kind or nature of rivalry that exists between them.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67fc237608190b6542b56038a7fe4 |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:30 p.m.