Triple
T22819357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DECT |
E565184
|
entity |
| Predicate | numberOfTimeSlotsPerFrame |
P149862
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [DECT, numberOfTimeSlotsPerFrame, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTimeSlotsPerFrame Context triple: [DECT, numberOfTimeSlotsPerFrame, 24]
-
A.
fieldsPerFrame
Indicates the number of discrete fields that compose each video frame in an interlaced video signal.
-
B.
frameDuration
Indicates the length of time that a single frame in a sequence (such as video or animation) is displayed before advancing to the next frame.
-
C.
timeFrameSpecified
Indicates that a specific temporal period or duration has been explicitly defined or constrained for the related event, action, or relationship.
-
D.
maxTheoreticalBandwidthPerSlot
Indicates the maximum possible data transfer capacity that can be achieved per individual slot under ideal conditions.
-
E.
numberOfFieldPeriods
Indicates the total count of distinct field periods associated with or occurring within a given context or 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dcf39a88190bec26affc304236d |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:33 p.m.