Triple
T8940350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utrecht Chair |
E212883
|
entity |
| Predicate | hasErgonomicType |
P86451
|
FINISHED |
| Object | lounge seating posture |
—
|
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: lounge seating posture | Statement: [Utrecht Chair, hasErgonomicType, lounge seating posture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasErgonomicType Context triple: [Utrecht Chair, hasErgonomicType, lounge seating posture]
-
A.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
B.
hasTouchCoverCompatibility
Indicates that one entity is compatible for use with a specific touch cover accessory associated with another entity.
-
C.
hasGripType
Indicates that one entity possesses or uses a specific type or style of grip in relation to another entity or action.
-
D.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
-
E.
hasArmrestType
Indicates the specific style or configuration of armrests associated with an item.
- F. None of above. chosen
Provenance (4 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b8b37c8190bce6e049de8cf732 |
completed | April 1, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc60e0d7208190966797ce5f95fe49 |
completed | April 1, 2026, 12:03 a.m. |
Created at: March 30, 2026, 6:58 p.m.