Triple
T419139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1974 FIFA World Cup |
E8060
|
entity |
| Predicate | numberOfQualifiedTeamsFromSouthAmerica |
P14679
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [1974 FIFA World Cup, numberOfQualifiedTeamsFromSouthAmerica, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfQualifiedTeamsFromSouthAmerica Context triple: [1974 FIFA World Cup, numberOfQualifiedTeamsFromSouthAmerica, 4]
-
A.
mostTeamsInCountry
Indicates that an entity has the highest number of teams located within a given country compared to all other entities.
-
B.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
C.
isOldestOngoingNationalSoccerTournamentIn
Indicates that a soccer tournament is the oldest continuously held national-level soccer competition within the specified country or region.
-
D.
nationalTeamAppearances
Indicates the number of official matches in which an entity has represented its national team.
-
E.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.