Triple
T35428853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campineiro Derby |
E1023997
|
entity |
| Predicate | countryDerbyContext |
P203656
|
FINISHED |
| Object | Brazilian football |
—
|
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: Brazilian football | Statement: [Campineiro Derby, countryDerbyContext, Brazilian football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryDerbyContext Context triple: [Campineiro Derby, countryDerbyContext, Brazilian football]
-
A.
countryDerbyStatus
Indicates the status or classification of a derby event within a particular country (e.g., whether it is recognized, active, or holds a specific official standing).
-
B.
countryOfRivalry
Indicates that one entity is a country with which another entity has a relationship of rivalry or adversarial competition.
-
C.
countryRivalryContext
Indicates a relationship where two countries are in a state of rivalry, competition, or conflict within a specific political, historical, or strategic context.
-
D.
cityDerbyHosted
Indicates that a particular city served as the host location for a specified derby event.
-
E.
cityDerby
Indicates a competitive or rivalry relationship between two cities, often in sports or similar local contests.
- F. None of above. chosen
Provenance (4 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a01beacf8a88190ac643a75c7a0efc4 |
completed | May 11, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_6a01be152c8c8190bb19d64a683e2aae |
completed | May 11, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_6a01beac1334819082be0e4cf017e00c |
completed | May 11, 2026, 11:34 a.m. |
Created at: May 3, 2026, 4:03 p.m.