Triple
T30428117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EF-M lens mount |
E774088
|
entity |
| Predicate | designedForBodySize |
P193840
|
FINISHED |
| Object | compact mirrorless bodies |
—
|
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 mirrorless bodies | Statement: [Canon EF-M lens mount, designedForBodySize, compact mirrorless bodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedForBodySize Context triple: [Canon EF-M lens mount, designedForBodySize, compact mirrorless bodies]
-
A.
bodySize
Indicates the relative physical magnitude or scale of an entity’s body, such as how large or small it is.
-
B.
designedForComfort
Indicates that something has been intentionally created or configured to enhance physical or psychological ease and reduce discomfort.
-
C.
sizeCategory
Indicates the relative size classification assigned to an entity compared to others (e.g., small, medium, large).
-
D.
bodyDesigner
Indicates that one entity is responsible for designing, shaping, or creating the physical form or structure of another entity.
-
E.
sizeDescription
Indicates a relationship where one entity provides descriptive information about the size or scale of 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
| PDg | Predicate description generation | batch_69fd57b9cdec81908536c4159e375931 |
completed | May 8, 2026, 3:25 a.m. |
Created at: April 29, 2026, 8:06 p.m.