Triple
T25177273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonah |
E630481
|
entity |
| Predicate | targetFormFactor |
P161443
|
FINISHED |
| Object | mobile workstations |
—
|
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: mobile workstations | Statement: [Yonah, targetFormFactor, mobile workstations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetFormFactor Context triple: [Yonah, targetFormFactor, mobile workstations]
-
A.
targetFormFactor
chosen
Indicates the specific physical configuration or design format that something is intended to be used with or fit into.
-
B.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
C.
deviceShape
Indicates that one entity has the physical form or geometric configuration specified by the other entity.
-
D.
supportsDriveFormFactor
Indicates that one entity is compatible with or can accommodate a specified physical form factor of a drive.
-
E.
targetedDevice
Indicates that one entity is the specific device toward which another entity’s action, effect, or configuration is directed.
- 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_69e75a88fdf081908e47ae6e195c14e1 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 21, 2026, 12:34 p.m.