Triple
T11352219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Level 3.1 |
E268863
|
entity |
| Predicate | hasMaxMBsPerFrameExample |
P99404
|
FINISHED |
| Object | 1280x720 uses 3600 macroblocks |
—
|
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: 1280x720 uses 3600 macroblocks | Statement: [Level 3.1, hasMaxMBsPerFrameExample, 1280x720 uses 3600 macroblocks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaxMBsPerFrameExample Context triple: [Level 3.1, hasMaxMBsPerFrameExample, 1280x720 uses 3600 macroblocks]
-
A.
frameSizeMaximum
Indicates the maximum allowable size or dimensions that a frame can have in a given context.
-
B.
propertyType_maxFramerate
Indicates the maximum frame rate value that the property can support or is configured to allow.
-
C.
maximumBitrate
Indicates the highest data transfer rate allowed or supported for a given media stream or connection.
-
D.
minimumFrameSize
Indicates the smallest allowable or supported size of a frame in the given context or system.
-
E.
maxDataTransferMode
Indicates the data transfer mode in which the maximum possible data throughput is achieved between entities.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
| PDg | Predicate description generation | batch_69d801451b1c8190944b17906b354142 |
completed | April 9, 2026, 7:43 p.m. |
Created at: April 8, 2026, 9:33 p.m.