Triple
T22819196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IS-136 |
E565181
|
entity |
| Predicate | numberOfTimeSlotsPerCarrier |
P149860
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [IS-136, numberOfTimeSlotsPerCarrier, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTimeSlotsPerCarrier Context triple: [IS-136, numberOfTimeSlotsPerCarrier, 3]
-
A.
maxTheoreticalBandwidthPerSlot
Indicates the maximum possible data transfer capacity that can be achieved per individual slot under ideal conditions.
-
B.
maxSlotsPerSystem
Indicates the maximum number of slots that are allowed or can be allocated within a single system.
-
C.
maximumStationsPerSegment
Indicates the greatest number of stations that are allowed or can exist within a single segment.
-
D.
maximumSlotsRecommended
Indicates the highest number of slots that is advised or suggested to be used in a given context.
-
E.
numberOfFrequencyBands
Indicates the relationship specifying how many distinct frequency bands are associated with or used by an 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_69f17dce762c8190934fb921f942c9fd |
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.