Triple
T30382419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EF-S lens mount |
E772865
|
entity |
| Predicate | electricalContacts |
P195642
|
FINISHED |
| Object | same as Canon EF mount |
—
|
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: same as Canon EF mount | Statement: [Canon EF-S lens mount, electricalContacts, same as Canon EF mount]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electricalContacts Context triple: [Canon EF-S lens mount, electricalContacts, same as Canon EF mount]
-
A.
electricalSystem
Indicates that one entity functions as, is part of, or is directly related to the electrical system of another entity.
-
B.
electricalPower
Indicates that one entity supplies, carries, or is associated with electrical power to or for another entity.
-
C.
hasElectricalProperty
Indicates that an entity possesses a specific electrical characteristic or behavior, such as conductivity, resistance, or charge-related properties.
-
D.
electricalPolarity
Indicates that there is a relationship specifying the direction or type of electrical charge or potential difference associated with an entity or connection.
-
E.
electronicComponents
Indicates a relationship where one entity consists of, contains, or is associated with specific electronic components.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_69fddd364c1481908794c9d423bdc2d7 |
completed | May 8, 2026, 12:55 p.m. |
Created at: April 29, 2026, 8:01 p.m.