Triple
T12305087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wix.com (offices) |
E293331
|
entity |
| Predicate | hasTypeOfWorkspace |
P32186
|
FINISHED |
| Object | open-plan offices |
—
|
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: open-plan offices | Statement: [Wix.com (offices), hasTypeOfWorkspace, open-plan offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfWorkspace Context triple: [Wix.com (offices), hasTypeOfWorkspace, open-plan offices]
-
A.
hasSpaceType
chosen
Indicates that one entity is associated with, or classified by, a particular type or category of space.
-
B.
hasSectionOfWorkType
Indicates that an entity is associated with a specific type or category of work section it involves or contains.
-
C.
hasProjectType
Indicates that an entity is associated with, or classified under, a specific type or category of project.
-
D.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
E.
typeOfWorkstation
Indicates the specific category or kind of workstation associated with an entity.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.