Triple
T218137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League |
E4152
|
entity |
| Predicate | mostTitlesClubTitles |
P2660
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Premier League, mostTitlesClubTitles, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostTitlesClubTitles Context triple: [Premier League, mostTitlesClubTitles, 13]
-
A.
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.
-
B.
hasMostSuccessfulFranchiseByTitles
Indicates that one entity is the franchise holding the highest number of titles (e.g., championships or awards) within a specified domain compared to all other franchises.
-
C.
mostSuccessfulFranchiseByTitles
chosen
Indicates the franchise that holds the highest number of titles (e.g., championships or equivalent honors) within a given context.
-
D.
team1ConferenceTitles
Indicates the number of conference championship titles won by the first team in a given context or comparison.
-
E.
worldSeriesTitles
Indicates the number of World Series championship titles an entity (typically a baseball team) has 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c5062e48190833be10e4770e1e9 |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5357bc8190b29a48e3053fb76d |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.