Triple
T485557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Cantona |
E9867
|
entity |
| Predicate | leagueTitleWonWithManchesterUnited |
P8189
|
FINISHED |
| Object | 1992-93 |
—
|
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: 1992-93 | Statement: [Eric Cantona, leagueTitleWonWithManchesterUnited, 1992-93]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueTitleWonWithManchesterUnited Context triple: [Eric Cantona, leagueTitleWonWithManchesterUnited, 1992-93]
-
A.
leagueTitlesWonWithManchesterUnited
chosen
Indicates the number of league titles an entity has won while playing for or managing Manchester United.
-
B.
faCupsWonWithManchesterUnited
Indicates the number of FA Cup titles an entity has won while playing for or managing Manchester United.
-
C.
communityShieldsWonWithManchesterUnited
Indicates the number of Community Shield titles an entity has won while playing for or managing Manchester United.
-
D.
majorTrophiesWithManchesterUnited
Indicates that the subject has won major football trophies while playing for or managing Manchester United.
-
E.
mostSuccessfulClub
Indicates that one club holds the highest level of success (e.g., by titles, achievements, or performance) compared to all other clubs in the given context.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0bb46788190b40182bf2a54f98f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.