Triple
T32377480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DVR-MS |
E827328
|
entity |
| Predicate | supportsTrickModes |
P206259
|
FINISHED |
| Object | pause |
—
|
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: pause | Statement: [DVR-MS, supportsTrickModes, pause]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTrickModes Context triple: [DVR-MS, supportsTrickModes, pause]
-
A.
supportsInterlacedVideo
Indicates that an entity is capable of handling, processing, or displaying interlaced video signals.
-
B.
supportsCinematicMode
Indicates that one entity provides or enables a cinematic mode feature for another entity.
-
C.
supportsNonInterlacedModes
Indicates that an entity is capable of handling or operating with non-interlaced (progressive) display modes.
-
D.
supportsFrameRates
Indicates that one entity is capable of operating with, handling, or being compatible with the specified frame rates of another entity.
-
E.
supportsInterlacing
Indicates that one entity is capable of handling or enabling interlaced data or processing for another entity.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:51 a.m.