Triple
T24955832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryukyuan scale |
E624469
|
entity |
| Predicate | hasIntervalStructure |
P162850
|
FINISHED |
| Object | pentatonic |
—
|
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: pentatonic | Statement: [Ryukyuan scale, hasIntervalStructure, pentatonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntervalStructure Context triple: [Ryukyuan scale, hasIntervalStructure, pentatonic]
-
A.
hasInterval
Indicates that something is associated with a specific span or range between two points in time, space, or value.
-
B.
hasBaseInterval
Indicates that one entity has a fundamental or reference interval that serves as the base measurement or range for another related quantity or structure.
-
C.
intervalPattern
Indicates a recurring temporal relationship where events or states follow a specific, regular interval pattern between their occurrences.
-
D.
invariantInterval
Indicates that a certain interval or range remains unchanged or constant under a specified transformation or set of conditions.
-
E.
supportsGuardIntervals
Indicates that one entity provides or is compatible with guard intervals used by another entity in a timing- or transmission-related context.
- 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_69e2ff23a3a88190b1b9743fe5e15f94 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f62e83045c8190a424a2e401a88e9e |
completed | May 2, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d886828819080ec2f742b9449e3 |
completed | May 2, 2026, 4:59 p.m. |
Created at: April 18, 2026, 5:57 a.m.