Triple
T641433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel 7 |
E16746
|
entity |
| Predicate | hasCameraBarDesign |
P1529
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pixel 7, hasCameraBarDesign, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCameraBarDesign Context triple: [Pixel 7, hasCameraBarDesign, yes]
-
A.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
-
B.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
C.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
D.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
-
E.
isBuiltFor
Indicates that one entity is specifically designed, intended, or optimized to serve, support, or accommodate another entity or purpose.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f02bc2c8190b8a92b2505768c19 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.