Triple
T2755804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghana national football team |
E61096
|
entity |
| Predicate | afconRunnersUpCount |
P41687
|
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: [Ghana national football team, afconRunnersUpCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afconRunnersUpCount Context triple: [Ghana national football team, afconRunnersUpCount, 5]
-
A.
WorldCupSemiFinalAppearances
Indicates the number of times an entity has reached the semi-final stage of a FIFA World Cup tournament.
-
B.
fifaWorldCupRunnersUpYear
Indicates the year in which an entity finished as runners-up in a FIFA World Cup tournament.
-
C.
WorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup final tournaments.
-
D.
worldCupRunnerUp
Indicates that an entity finished in second place in a FIFA World Cup tournament.
-
E.
numberOfFIFAConfederations
Indicates the total count of FIFA confederations associated with a given 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb718f4c8190bfc34c6597163ebc |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd82d005c81908a1ac7a1313c6d88 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd91497ec8190927e91ad33549eda |
completed | March 7, 2026, 7:51 a.m. |
Created at: March 6, 2026, 9:56 p.m.