Triple
T32752959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulster Senior Football Championship |
E837545
|
entity |
| Predicate | mostSuccessfulCountyTitles |
P25122
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Ulster Senior Football Championship, mostSuccessfulCountyTitles, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostSuccessfulCountyTitles Context triple: [Ulster Senior Football Championship, mostSuccessfulCountyTitles, 40]
-
A.
mostSuccessfulCounty
Indicates that a given county is the one with the highest level of success (according to some defined metric) within a specified group or context.
-
B.
countyChampionshipTitles
Indicates the number of county-level championship titles an entity has won.
-
C.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
D.
runnerUpMostTitles
Indicates that an entity holds the record for having the highest number of runner-up finishes or second-place titles in a given competition or context.
-
E.
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.
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:12 a.m.