Triple
T16261682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | England 1966 FIFA World Cup squad |
E394768
|
entity |
| Predicate | worldCupTitlesAfterTournament |
P98946
|
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: [England 1966 FIFA World Cup squad, worldCupTitlesAfterTournament, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldCupTitlesAfterTournament Context triple: [England 1966 FIFA World Cup squad, worldCupTitlesAfterTournament, 1]
-
A.
WorldCupOverallTitles
Indicates the total number of World Cup championship titles an entity has won across all tournaments.
-
B.
worldCupWon
Indicates that the subject has won the FIFA World Cup tournament.
-
C.
worldCupSeasonTitles
Indicates the number or list of World Cup season titles associated with an entity (such as a team, player, or nation).
-
D.
numberOfWorldCupWins
chosen
Indicates how many times an entity has won the FIFA World Cup tournament.
-
E.
WorldCupSeasonTitles
Indicates the number of World Cup titles an entity has won in a given season or across seasons.
- F. None of above.
Provenance (3 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c4a0b08190af3574f087205afc |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.