Triple
T25426456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FH9 |
E637127
|
entity |
| Predicate | typicalMimeType |
P55167
|
FINISHED |
| Object | application/x-freehand |
—
|
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: application/x-freehand | Statement: [FH9, typicalMimeType, application/x-freehand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMimeType Context triple: [FH9, typicalMimeType, application/x-freehand]
-
A.
typicalMIMEType
chosen
Indicates the standard or most commonly used MIME (media) type associated with a given resource or format.
-
B.
typicalFileType
Indicates that one entity is the usual or commonly associated file type for the other entity.
-
C.
typicalFileFormat
Indicates the usual or standard file format typically associated with or used for a given entity or context.
-
D.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
E.
typicalPictureFormat
Indicates the standard or most commonly used picture format associated with an entity (such as a device, medium, or context).
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 21, 2026, 1:57 p.m.