Triple
T1713509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secretaries of State of Belgium |
E37236
|
entity |
| Predicate | hasTypeOf |
P16808
|
FINISHED |
| Object | sub-ministerial office |
—
|
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: sub-ministerial office | Statement: [Secretaries of State of Belgium, hasTypeOf, sub-ministerial office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOf Context triple: [Secretaries of State of Belgium, hasTypeOf, sub-ministerial office]
-
A.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
typeOf
Indicates that one entity is a specific kind, class, or category instance of another more general entity.
-
C.
hasTypeOfResource
Indicates that an entity is associated with a specific category or kind of resource it represents or utilizes.
-
D.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
-
E.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.