Triple
T32524056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel I Government |
E831260
|
entity |
| Predicate | secretaryOfState |
P23783
|
FINISHED |
| Object | Theo Francken |
—
|
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: Theo Francken | Statement: [Michel I Government, secretaryOfState, Theo Francken]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secretaryOfState Context triple: [Michel I Government, secretaryOfState, Theo Francken]
-
A.
firstSecretaryOfState
Indicates that the subject is the first person to have held the position of Secretary of State for the specified entity.
-
B.
succeededInOfficeAsSecretaryOfStateBy
Indicates that one individual was followed in the role of Secretary of State by another individual, who took over the office after them.
-
C.
stateSecretary
chosen
Indicates that one entity holds or is associated with the position of state secretary in relation to another entity (such as a government, state, or administration).
-
D.
currentSecretary
Indicates that one entity currently holds the position or role of secretary for another entity.
-
E.
precededInOfficeAsSecretaryOfStateBy
Indicates that one person assumed the role of Secretary of State after another specific person, who held the office immediately before them.
- 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c516640c81909fce8dc8240a00a9 |
completed | May 3, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:01 a.m.