Triple
T11349511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoweri Museveni |
E268803
|
entity |
| Predicate | hasElectionsContestedAsPresident |
P36644
|
FINISHED |
| Object | multiple Ugandan general elections |
—
|
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: multiple Ugandan general elections | Statement: [Yoweri Museveni, hasElectionsContestedAsPresident, multiple Ugandan general elections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectionsContestedAsPresident Context triple: [Yoweri Museveni, hasElectionsContestedAsPresident, multiple Ugandan general elections]
-
A.
wasContestedIn
Indicates that an event, position, or decision was the subject of competition, dispute, or challenge within a particular context or proceeding.
-
B.
wonPresidentialElection
Indicates that one entity achieved victory over others in a presidential election.
-
C.
wasContestedBetween
Indicates that an event, position, or resource was the subject of competition or dispute involving two or more opposing parties.
-
D.
hasOfficeContested
chosen
Indicates that an individual has been a candidate for a particular public office in an election.
-
E.
hasPresidentBeforeElection
Indicates that an entity already has a designated or acting president prior to a specified election event.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.