Triple
T1296963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet Championship League |
E27674
|
entity |
| Predicate | numberOfTitlesWonByMostSuccessfulClub |
P25334
|
FINISHED |
| Object | 32 |
—
|
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: 32 | Statement: [Soviet Championship League, numberOfTitlesWonByMostSuccessfulClub, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTitlesWonByMostSuccessfulClub Context triple: [Soviet Championship League, numberOfTitlesWonByMostSuccessfulClub, 32]
-
A.
isOneOfMostSuccessfulClubsIn
Indicates that a club ranks among the most successful clubs within a specified group, region, or competition context.
-
B.
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.
-
C.
UEFAChampionsLeagueTitles
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
D.
numberOfCoppaItaliaTitles
Indicates the quantity of Coppa Italia titles that an entity has won.
-
E.
mostDivisionTitlesTeam
chosen
Indicates that the subject team holds the record for having won the greatest number of division titles compared to all other teams.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.