Triple
T658129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macintosh SE |
E11692
|
entity |
| Predicate | caseDesign |
P1529
|
FINISHED |
| Object | compact all-in-one beige case |
—
|
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: compact all-in-one beige case | Statement: [Macintosh SE, caseDesign, compact all-in-one beige case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseDesign Context triple: [Macintosh SE, caseDesign, compact all-in-one beige case]
-
A.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
-
C.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
-
D.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
-
E.
cantonDesign
Indicates that a canton (administrative region) is responsible for designing or determining the form, structure, or layout of something.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fa55e048190bd9913c6c31772d0 |
completed | March 1, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69a49d121cec81909986c91291bb4ca8 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.