Triple
T15870087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AS Monaco FC |
E384808
|
entity |
| Predicate | Ligue1Titles |
P120841
|
FINISHED |
| Object | multiple |
—
|
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 | Statement: [AS Monaco FC, Ligue1Titles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Ligue1Titles Context triple: [AS Monaco FC, Ligue1Titles, multiple]
-
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.
Ligue1TitleSeason
Indicates the relationship between a Ligue 1 football title and the specific season in which that title was won.
-
C.
numberOfCoupeDeLaLigueTitles
Indicates the total count of Coupe de la Ligue titles that an entity has won.
-
D.
coupeDeLaLigueTitle
Indicates that an entity has won a Coupe de la Ligue championship title.
-
E.
numberOfCoupeDeFranceTitles
Indicates the total count of Coupe de France titles that an entity has 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:50 a.m.