Triple
T23159238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2002 FIFA World Cup Final |
E578532
|
entity |
| Predicate | resultingTitleCountForBrazil |
P151148
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [2002 FIFA World Cup Final, resultingTitleCountForBrazil, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultingTitleCountForBrazil Context triple: [2002 FIFA World Cup Final, resultingTitleCountForBrazil, 5]
-
A.
titleInPortuguese
Indicates that an entity has a specific title expressed in the Portuguese language.
-
B.
equivalentTitleInPortuguese
Indicates that one entity has a title that is the equivalent of another entity’s title, specifically in Portuguese.
-
C.
significantPopulationInBrazilianState
Indicates that a population group or entity has a notably large or important presence within a specific Brazilian state.
-
D.
nameInBrazil
Indicates that an entity is known or referred to by a particular name specifically in the context of Brazil.
-
E.
eraTitleCount
Indicates the number of distinct titles associated with a given era.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18eff965081909aaa6fc1910293e2 |
completed | April 29, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:02 p.m.