Triple
T24512305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unia Leszno |
E606257
|
entity |
| Predicate | numberOfPolishChampionshipTitles |
P97962
|
FINISHED |
| Object | many |
—
|
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: many | Statement: [Unia Leszno, numberOfPolishChampionshipTitles, many]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPolishChampionshipTitles Context triple: [Unia Leszno, numberOfPolishChampionshipTitles, many]
-
A.
numberOfPolishChampionships
chosen
Indicates the total count of Polish championship titles associated with an entity.
-
B.
PolishCupTitlesSeason
Indicates the number of Polish Cup titles a team has won in a given season.
-
C.
numberOfDFBPokalTitles
Indicates the number of DFB-Pokal titles that an entity has won.
-
D.
numberOfCzechoslovakTitles
Indicates the number of titles or championships an entity has won in Czechoslovakia.
-
E.
divisionTitlesWonWith
Indicates that one entity has won a specified number of division titles in association with another entity (such as a team, league, or organization).
- 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_69e2c4c725148190a4e41577c5cb409c |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:24 a.m.