Triple
T11834395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Division 1972–73 |
E281476
|
entity |
| Predicate | championsTitleCountForClub |
P27144
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [First Division 1972–73, championsTitleCountForClub, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championsTitleCountForClub Context triple: [First Division 1972–73, championsTitleCountForClub, 8]
-
A.
mostChampionshipTitlesClub
Indicates that a club holds the highest number of championship titles within a given competition or context.
-
B.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
-
C.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
D.
UEFAChampionsLeagueTitles
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
E.
numberOfTitlesOfMostSuccessfulClub
chosen
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.
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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62e7e408190998bebe346c82e89 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.