Triple
T35068979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cercle Saint-Pierre Limoges |
E1011813
|
entity |
| Predicate | nationalChampionshipTitles |
P18665
|
FINISHED |
| Object | multiple French League titles |
—
|
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: multiple French League titles | Statement: [Cercle Saint-Pierre Limoges, nationalChampionshipTitles, multiple French League titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalChampionshipTitles Context triple: [Cercle Saint-Pierre Limoges, nationalChampionshipTitles, multiple French League titles]
-
A.
nationalChampionshipTitle
chosen
Indicates that an entity has won a national-level championship title in a particular sport, competition, or field.
-
B.
numberOfNationalChampionships
Indicates the total count of national championship titles an entity has won.
-
C.
nationalChampionshipParticipation
Indicates that an entity has taken part in a national-level championship competition.
-
D.
NCAAChampionshipCount
Indicates the number of NCAA championships an entity has won.
-
E.
FAcupTitles
Indicates that an entity has won a specified number of FA Cup titles.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: May 3, 2026, 4:01 p.m.