Triple
T4065797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAD750 |
E86319
|
entity |
| Predicate | boardFormFactor |
P9336
|
FINISHED |
| Object | single-board computer |
—
|
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: single-board computer | Statement: [RAD750, boardFormFactor, single-board computer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardFormFactor Context triple: [RAD750, boardFormFactor, single-board computer]
-
A.
hasFormFactor
chosen
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
B.
סוג לוח
Indicates a relationship specifying the type or category of a board (e.g., board format, board kind, or board classification) associated with an entity.
-
C.
tabletCount
Indicates the number of tablets associated with or allocated to a given entity or context.
-
D.
plateType
Indicates the specific category or style of plate associated with an item or context.
-
E.
device
Indicates that one entity is a device used, controlled, or referenced by another entity in the relationship.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf58d9c8190936e453b0d397cb0 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.