Triple
T27619062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compact Disc |
E700518
|
entity |
| Predicate | audioCapacity |
P162759
|
FINISHED |
| Object | approximately 80 minutes |
—
|
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 80 minutes | Statement: [Compact Disc, audioCapacity, approximately 80 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioCapacity Context triple: [Compact Disc, audioCapacity, approximately 80 minutes]
-
A.
audioCapacity
chosen
Indicates the maximum amount or quality of audio data that something can handle, store, or transmit.
-
B.
audioChannels
Indicates the number or configuration of distinct audio signal paths (such as mono, stereo, or surround) used in a recording, transmission, or playback.
-
C.
haveLimitedNumberOfSpeakers
Indicates that the language or communication system is used fluently by only a relatively small number of speakers.
-
D.
audioChannelsType
Indicates the type or configuration of audio channels used in an audio signal or recording (e.g., mono, stereo, surround).
-
E.
hasNumberOfSpeakersCategory
Indicates a classification of an entity based on the number of speakers associated with it, typically grouping it into predefined size categories.
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 2:13 p.m.