Triple
T35068980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cercle Saint-Pierre Limoges |
E1011813
|
entity |
| Predicate | FrenchLeagueTitle |
P55373
|
FINISHED |
| Object | 1983 |
—
|
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: 1983 | Statement: [Cercle Saint-Pierre Limoges, FrenchLeagueTitle, 1983]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchLeagueTitle Context triple: [Cercle Saint-Pierre Limoges, FrenchLeagueTitle, 1983]
-
A.
FrenchLeagueTitlesWith
Indicates a relationship where two entities are associated through having won French football league titles together (e.g., a club and a player sharing those titles).
-
B.
Ligue1Titles
Indicates the number of Ligue 1 championship titles an entity has won.
-
C.
Ligue1TitleSeason
chosen
Indicates the relationship between a Ligue 1 football title and the specific season in which that title was won.
-
D.
coupeDeLaLigueTitle
Indicates that an entity has won a Coupe de la Ligue championship title.
-
E.
CoupeDeFranceTitleSeason
Indicates the specific season in which a Coupe de France title was won.
- 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_69f7861a3eb481909f9bd86edbbc3947 |
completed | May 3, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.