Triple
T419142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1974 FIFA World Cup |
E8060
|
entity |
| Predicate | numberOfQualifiedTeamsFromAsiaOceania |
P14682
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1974 FIFA World Cup, numberOfQualifiedTeamsFromAsiaOceania, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfQualifiedTeamsFromAsiaOceania Context triple: [1974 FIFA World Cup, numberOfQualifiedTeamsFromAsiaOceania, 1]
-
A.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
numberOfPlayoffTeams
Indicates the total count of teams that qualify for or participate in the playoffs within a given league or season.
-
C.
advancesNumberOfTeams
Indicates that one entity causes an increase in how many teams progress or move forward in a given context.
-
D.
numberOfTeamsInCanada
Indicates the total count of teams that are located in Canada.
-
E.
typicalNumberOfCWSTeams
Indicates the usual or standard number of CWS teams associated with or involved in a given context or entity.
- 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.