Triple
T15377465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Arab Emirates national football team |
E367705
|
entity |
| Predicate | afcAsianCupBestResult |
P58031
|
FINISHED |
| Object | Runners-up 1996 |
—
|
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: Runners-up 1996 | Statement: [United Arab Emirates national football team, afcAsianCupBestResult, Runners-up 1996]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afcAsianCupBestResult Context triple: [United Arab Emirates national football team, afcAsianCupBestResult, Runners-up 1996]
-
A.
wonAsianCupWinnersCup
Indicates that one entity (typically a sports team or club) has won the Asian Cup Winners' Cup competition.
-
B.
asiaCupWinner
Indicates that one entity is the champion or winning team of the Asia Cup tournament in a given edition or year.
-
C.
asiaCupBestPerformance
chosen
Indicates the best result or highest achievement an entity has attained in the Asia Cup competition.
-
D.
asianCupAppearances
Indicates the number of times an entity has participated in the AFC Asian Cup tournament.
-
E.
africaCupOfNationsBestResult
Indicates the best performance or highest achievement a team or participant has attained in the Africa Cup of Nations tournament.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e5ece1081908d7c1289258b9c1f |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:18 a.m.