Triple
T37337301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janet Kataaha Museveni |
E926928
|
entity |
| Predicate | marriedToHeadOfGovernment |
P195710
|
FINISHED |
| Object | Yoweri Kaguta Museveni |
—
|
NE NERFINISHED |
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: Yoweri Kaguta Museveni | Statement: [Janet Kataaha Museveni, marriedToHeadOfGovernment, Yoweri Kaguta Museveni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToHeadOfGovernment Context triple: [Janet Kataaha Museveni, marriedToHeadOfGovernment, Yoweri Kaguta Museveni]
-
A.
marriedToHeadOfGovernmentOf
Indicates that one entity is the spouse of the person who holds the position of head of government of the other entity.
-
B.
spouseOfHeadOfState
Indicates that one person is the spouse (married partner) of a head of state.
-
C.
marriedToPrimeMinisterDuring
Indicates that one person was married to the individual serving as prime minister during a specified time period.
-
D.
marriedToPolitician
Indicates that a person is married to someone who holds or has held a political office or role.
-
E.
spouseOfLeader
Indicates that one entity is the married partner (spouse) of another entity who holds a leadership position.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: May 3, 2026, 4:16 p.m.