Triple
T31295321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bibendum chair |
E798056
|
entity |
| Predicate | hasSeatForm |
P125940
|
FINISHED |
| Object | stacked cylindrical cushions |
—
|
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: stacked cylindrical cushions | Statement: [Bibendum chair, hasSeatForm, stacked cylindrical cushions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatForm Context triple: [Bibendum chair, hasSeatForm, stacked cylindrical cushions]
-
A.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
B.
seatForm
chosen
Indicates that one entity serves as the physical seating structure or configuration associated with another entity.
-
C.
hasSeatBuilding
Indicates that a seat (or seating area) is located within or belongs to a particular building.
-
D.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
E.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given context.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: April 29, 2026, 9:14 p.m.