Triple
T5469191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelso Dunes |
E122787
|
entity |
| Predicate | soundFrequencyRange |
P64259
|
FINISHED |
| Object | typically around 70–110 Hz |
—
|
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: typically around 70–110 Hz | Statement: [Kelso Dunes, soundFrequencyRange, typically around 70–110 Hz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundFrequencyRange Context triple: [Kelso Dunes, soundFrequencyRange, typically around 70–110 Hz]
-
A.
typicalRangeSubsonic
Indicates that the relationship specifies the usual or expected range of values or conditions that apply in a subsonic (below the speed of sound) regime.
-
B.
vocalRange
Indicates the span of pitches or notes that an entity (such as a singer or instrument) is capable of producing.
-
C.
audioSampleRateHz
Indicates the number of audio samples captured or played back per second, measured in hertz (Hz), for the associated audio data.
-
D.
soundHardware
Indicates that an entity is associated with, uses, or provides sound-related hardware components or capabilities.
-
E.
audioSampleRates
Indicates the relationship between an audio resource and the sample rate(s) at which that audio is encoded or can be processed.
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd927b0b4c81909d5e0f594822e3f9 |
completed | March 20, 2026, 6:31 p.m. |
Created at: March 20, 2026, 2:09 p.m.