Triple
T32377479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DVR-MS |
E827328
|
entity |
| Predicate | supportsTimeShifting |
P206258
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [DVR-MS, supportsTimeShifting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTimeShifting Context triple: [DVR-MS, supportsTimeShifting, yes]
-
A.
supportsTimeStretch
Indicates that one entity provides the capability to alter the duration of another entity (such as audio or video) without changing its pitch.
-
B.
timeShiftService
Indicates that a service is provided with a shifted or delayed time relative to its original or real-time schedule.
-
C.
supportsTimecodes
Indicates that one entity can handle, interpret, or work with timecode information associated with another entity or data stream.
-
D.
supportsTimescale
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
-
E.
timeShiftProperty
Indicates a relationship where one property value is derived from another by applying a temporal shift (e.g., offsetting it to an earlier or later point in time).
- 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.