Triple
T37671068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belarus and Latvia |
E937957
|
entity |
| Predicate | yearOfCoHostedChampionship |
P197220
|
FINISHED |
| Object | 2021 |
—
|
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: 2021 | Statement: [Belarus and Latvia, yearOfCoHostedChampionship, 2021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfCoHostedChampionship Context triple: [Belarus and Latvia, yearOfCoHostedChampionship, 2021]
-
A.
openChampionshipHostYears
Indicates the years during which a given entity served as the host for an Open Championship event.
-
B.
numberOfOpenChampionshipsHosted
Indicates the count of Open Championship golf tournaments that have been hosted by a given entity.
-
C.
championshipHeld
Indicates that a championship event took place or was hosted at a particular time and/or location.
-
D.
championshipEndYear
Indicates the calendar year in which a particular championship or title-holding period concludes.
-
E.
associatedChampionshipCount
Indicates the number of championships that are linked or related to a given entity.
- F. None of above. chosen
Provenance (4 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
| PDg | Predicate description generation | batch_69fe7bfb71b08190bed5c33e4ab7afff |
completed | May 9, 2026, 12:12 a.m. |
Created at: May 3, 2026, 4:18 p.m.