Triple
T8414511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac 68k bootloaders |
E198700
|
entity |
| Predicate | loadsFromMedium |
P43634
|
FINISHED |
| Object | floppy disk |
—
|
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: floppy disk | Statement: [Mac 68k bootloaders, loadsFromMedium, floppy disk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loadsFromMedium Context triple: [Mac 68k bootloaders, loadsFromMedium, floppy disk]
-
A.
loadingMechanism
Indicates the method or system by which something is loaded into or onto another object or structure.
-
B.
loadBearingFor
Indicates that one entity structurally supports and carries the weight or load of another entity.
-
C.
loadType
Indicates the manner or category of how something is loaded, such as the method, configuration, or type of loading applied in a given context.
-
D.
isFromMedium
Indicates that something originates from, is derived from, or was obtained via a particular medium or channel.
-
E.
readsFrom
chosen
Indicates that one entity obtains or accesses data, information, or content from another entity as a source.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e328cc8190b3b038005d0bb66f |
completed | March 31, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.