Triple
T15652891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strictly The Best |
E376355
|
entity |
| Predicate | typicalTrackCountPerVolume |
P1707
|
FINISHED |
| Object | approximately 15 to 20 tracks |
—
|
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: approximately 15 to 20 tracks | Statement: [Strictly The Best, typicalTrackCountPerVolume, approximately 15 to 20 tracks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrackCountPerVolume Context triple: [Strictly The Best, typicalTrackCountPerVolume, approximately 15 to 20 tracks]
-
A.
numberOfTracks
chosen
Indicates the quantity of tracks associated with a given entity.
-
B.
sectorCountPerTrack
Indicates the number of data sectors that are contained on each individual track of a storage medium.
-
C.
numberOfGrooves
Indicates the count of grooves or channels present on or within an object or surface.
-
D.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
-
E.
bandCount
Indicates the number of bands or distinct grouped units associated with a given entity.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef089948190902ec22f4d7bc932 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.