Triple
T25426211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ALAC |
E637122
|
entity |
| Predicate | supportsBitDepthUpTo |
P179180
|
FINISHED |
| Object | 32-bit |
—
|
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: 32-bit | Statement: [ALAC, supportsBitDepthUpTo, 32-bit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBitDepthUpTo Context triple: [ALAC, supportsBitDepthUpTo, 32-bit]
-
A.
supportsAlphaBitDepth
Indicates that one entity is capable of handling or providing image or video data with an alpha (transparency) channel at a specified bit depth.
-
B.
colorDepth
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
-
C.
videoBitDepthInternal
Indicates the number of bits used internally to represent each color component of video data during processing or storage.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
usesBitplanes
Indicates that one entity employs a bitplane-based representation or processing method in relation to another entity or data.
- F. None of above. chosen
Provenance (4 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_69f7201e241c819092d56a7bb99dc94d |
completed | May 3, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71f8df5d48190944fbfbd9d573868 |
completed | May 3, 2026, 10:12 a.m. |
Created at: April 21, 2026, 1:57 p.m.