Triple
T8933981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Weah |
E212727
|
entity |
| Predicate | yearOfAward_African_Footballer_of_the_Year |
P86276
|
FINISHED |
| Object | 1989 |
—
|
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: 1989 | Statement: [George Weah, yearOfAward_African_Footballer_of_the_Year, 1989]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfAward_African_Footballer_of_the_Year Context triple: [George Weah, yearOfAward_African_Footballer_of_the_Year, 1989]
-
A.
BallonDorYear
Indicates the specific year in which a Ballon d'Or award was given.
-
B.
fifaWorldPlayerOfTheYear
Indicates that one entity has been awarded the FIFA World Player of the Year title for a given year or period.
-
C.
FIFABallonDorWinner
Indicates that the subject is the football player who won the FIFA Ballon d'Or award in the specified year or context.
-
D.
StateOfOriginManOfTheMatchAwards
Indicates the number of Man of the Match awards a player has received in State of Origin matches.
-
E.
afconTitleYear
Indicates the specific year in which a given Africa Cup of Nations (AFCON) title was won.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668fa87c8190bfeda820368b89e4 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc608331f88190bcb500ff63527f8a |
completed | April 1, 2026, 12:02 a.m. |
Created at: March 30, 2026, 6:57 p.m.