Triple
T3575928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexanderson alternator |
E75687
|
entity |
| Predicate | notableFrequency |
P49801
|
FINISHED |
| Object | 17.2 kHz |
—
|
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: 17.2 kHz | Statement: [Alexanderson alternator, notableFrequency, 17.2 kHz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFrequency Context triple: [Alexanderson alternator, notableFrequency, 17.2 kHz]
-
A.
notableDuring
Indicates that something was especially prominent, active, or significant during a particular time period or event.
-
B.
hasFrequencyNote
Indicates that something is associated with a specific note describing how often it occurs or is repeated.
-
C.
notableRepeatBy
Indicates that an action, event, or pattern occurs repeatedly and is notably performed, exhibited, or instantiated by a particular entity.
-
D.
notableVolume
Indicates that an entity is a significant or well-known volume (such as a book or written work) associated with another entity.
-
E.
notableSingle
Indicates that the subject is particularly recognized or distinguished for one specific, individual instance (such as a single work, event, or achievement).
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0da77008190922f414b85b9cad4 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb8e4ba948190a9b777cf7f788b96 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:21 p.m.