Triple
T6789727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JPEG |
E155901
|
entity |
| Predicate | widelyUsedOn |
P2367
|
FINISHED |
| Object | digital cameras |
—
|
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: digital cameras | Statement: [JPEG, widelyUsedOn, digital cameras]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widelyUsedOn Context triple: [JPEG, widelyUsedOn, digital cameras]
-
A.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
B.
usedOn
chosen
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
C.
isFamouslyUsedBy
Indicates that something is widely and notably used by a particular person, group, or entity, in a way that is broadly recognized or associated with them.
-
D.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
E.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ab4ce88190b6311e4d5aac758c |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.