Triple
T3876956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel 9 Pro Fold |
E92523
|
entity |
| Predicate | hasCameraFeature |
P17640
|
FINISHED |
| Object | computational photography |
—
|
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: computational photography | Statement: [Pixel 9 Pro Fold, hasCameraFeature, computational photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCameraFeature Context triple: [Pixel 9 Pro Fold, hasCameraFeature, computational photography]
-
A.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
B.
hasWideCamera
Indicates that an entity is equipped with or features a wide-angle camera.
-
C.
hasInnerSelfieCamera
Indicates that an object (typically a device) is equipped with a front-facing or inward-facing selfie camera.
-
D.
hasOuterSelfieCamera
Indicates that an entity (typically a device) is equipped with a front-facing camera intended for taking selfies.
-
E.
hasAIPhotoFeatures
chosen
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.