Triple
T30949415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α7R V |
E788493
|
entity |
| Predicate | contrastDetectionPoints |
P194709
|
FINISHED |
| Object | 425 contrast-detection points |
—
|
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: 425 contrast-detection points | Statement: [Sony α7R V, contrastDetectionPoints, 425 contrast-detection points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastDetectionPoints Context triple: [Sony α7R V, contrastDetectionPoints, 425 contrast-detection points]
-
A.
contrastAFPoints
Indicates a relationship where autofocus points are compared or differentiated to highlight their differences or opposing characteristics.
-
B.
contrastCharacteristic
Indicates that two entities are being compared by highlighting opposing or significantly different characteristics between them.
-
C.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
-
D.
contrastExplanation
Indicates an explanation that highlights differences between two or more entities, ideas, or situations by contrasting them.
-
E.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
- F. None of above. chosen
Provenance (4 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
| PDg | Predicate description generation | batch_69fd82ebe1c081908455fc45b6e45178 |
completed | May 8, 2026, 6:30 a.m. |
Created at: April 29, 2026, 8:53 p.m.