Triple
T29266844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campeonato Brasileiro Série D |
E741998
|
entity |
| Predicate | usesAggregateScoreInKnockouts |
P171809
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Campeonato Brasileiro Série D, usesAggregateScoreInKnockouts, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAggregateScoreInKnockouts Context triple: [Campeonato Brasileiro Série D, usesAggregateScoreInKnockouts, true]
-
A.
recordAggregateScore
Indicates recording a combined or total score derived from multiple individual scores or components.
-
B.
quarterFinalAggregateScore
Indicates the combined total score for an entity across all legs or matches in a quarter-final round of a competition.
-
C.
usesCompositeScore
Indicates that an entity bases its evaluation, decision, or outcome on a combined score derived from multiple underlying metrics or factors.
-
D.
numberOfKnockouts
Indicates the total count of times an entity has defeated opponents by knockout.
-
E.
useTiebreakers
Indicates that when primary criteria result in a tie, additional predefined rules or factors are applied to determine a winner or ordering.
- 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_69f0912065c08190bddd23e20e8ef18e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 28, 2026, 12:45 p.m.