Triple
T17417507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VP9 |
E423522
|
entity |
| Predicate | compressionEfficiencyComparedToH264 |
P127373
|
FINISHED |
| Object | higher at same visual quality |
—
|
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: higher at same visual quality | Statement: [VP9, compressionEfficiencyComparedToH264, higher at same visual quality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionEfficiencyComparedToH264 Context triple: [VP9, compressionEfficiencyComparedToH264, higher at same visual quality]
-
A.
advantageOverMPEG-PS
Indicates that one entity has a benefit or superiority compared to MPEG-PS in some aspect or use case.
-
B.
compressionLoss
Indicates that some amount of information, quality, or fidelity is lost as a result of a compression process.
-
C.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
D.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
E.
supportsHEVCEncode
Indicates that one entity provides the capability for another entity to perform HEVC (High Efficiency Video Coding) encoding.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44233c7888190a4d2aa703b206851 |
completed | April 19, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a33e8481908fa6ef45290d08aa |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:46 a.m.