Triple
T31295322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bibendum chair |
E798056
|
entity |
| Predicate | hasBackrestForm |
P14113
|
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, hasBackrestForm, stacked cylindrical cushions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackrestForm Context triple: [Bibendum chair, hasBackrestForm, stacked cylindrical cushions]
-
A.
hasBackrest
Indicates that one entity (typically a seat or seating object) includes or is equipped with a supporting backrest.
-
B.
hasBackrestType
chosen
Indicates the specific kind or style of backrest that an object (typically a seat or chair) possesses.
-
C.
hasArmrestType
Indicates the specific style or configuration of armrests associated with an item.
-
D.
chairType
Indicates the specific kind or category of chair that an entity is classified as.
-
E.
hasSeatBase
Indicates that an object possesses or is equipped with a seat base component.
- 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_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 29, 2026, 9:14 p.m.