Triple
T32582749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Cross of the Order of Leopold |
E832832
|
entity |
| Predicate | hasOrderSeat |
P3522
|
FINISHED |
| Object | Brussels |
—
|
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: Brussels | Statement: [Grand Cross of the Order of Leopold, hasOrderSeat, Brussels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrderSeat Context triple: [Grand Cross of the Order of Leopold, hasOrderSeat, Brussels]
-
A.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given context.
-
B.
hasSeat
chosen
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
D.
hasSeatSince
Indicates that an entity has continuously held a particular seat or position starting from a specified point in time.
-
E.
orderSeat
Indicates that an entity reserves or requests a specific seat (e.g., in a venue, vehicle, or event) for use.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: May 1, 2026, 1:04 a.m.