Triple
T4217744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Nantes |
E94260
|
entity |
| Predicate | numberOfCoupeDeLaLigueTitles |
P55376
|
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: [FC Nantes, numberOfCoupeDeLaLigueTitles, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoupeDeLaLigueTitles Context triple: [FC Nantes, numberOfCoupeDeLaLigueTitles, 1]
-
A.
UEFAChampionsLeagueTitles
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
B.
UEFAEuropaLeagueTitles
Indicates the number of UEFA Europa League championship titles an entity has won.
-
C.
numberOfCoppaItaliaTitles
Indicates the quantity of Coppa Italia titles that an entity has won.
-
D.
consecutiveLeagueTitles
Indicates that one entity has won league titles in successive seasons without interruption.
-
E.
numberOfTitlesOfMostSuccessfulClub
Indicates the total count of titles won by the club that has achieved the highest number of titles among all clubs in the given context.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e4ace648190acf911853d4fcf86 |
completed | March 12, 2026, 11:37 p.m. |
Created at: March 12, 2026, 11:04 p.m.