Triple
T32026896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DMR |
E817841
|
entity |
| Predicate | numberOfFrequencyChannels |
P123775
|
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: [DMR, numberOfFrequencyChannels, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFrequencyChannels Context triple: [DMR, numberOfFrequencyChannels, 3]
-
A.
numberOfFrequencyBands
Indicates the relationship specifying how many distinct frequency bands are associated with or used by an entity.
-
B.
hasFrequencyChannels
Indicates that an entity is associated with, or operates over, one or more specific frequency channels.
-
C.
numberOfFullRangeChannels
Indicates the total count of channels that operate over the complete available range of values or frequencies.
-
D.
numberOfAdditionalChannels
Indicates the quantity of extra channels added beyond a base or default set in a given context.
-
E.
numberOfSpectralChannels
chosen
Indicates the relationship specifying how many distinct spectral channels are associated with an entity or measurement.
- F. None of above.
Provenance (3 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a017a360f088190acd5933aa353e763 |
completed | May 11, 2026, 6:41 a.m. |
| PD | Predicate disambiguation | batch_6a0179d3f78c8190b1d2e8829619fa54 |
completed | May 11, 2026, 6:40 a.m. |
Created at: May 1, 2026, 12:17 a.m.