Triple
T15602117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pythagorean tuning |
E375058
|
entity |
| Predicate | usesIntervalRatio |
P119404
|
FINISHED |
| Object | 3:2 |
—
|
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: 3:2 | Statement: [Pythagorean tuning, usesIntervalRatio, 3:2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesIntervalRatio Context triple: [Pythagorean tuning, usesIntervalRatio, 3:2]
-
A.
hasInterval
Indicates that something is associated with a specific span or range between two points in time, space, or value.
-
B.
originalTimeInterval
Indicates the initial or primary time span during which an event, state, or relationship is considered to occur, before any adjustments or derived intervals.
-
C.
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.
-
D.
unitIntervalEquals
Indicates that two values are equal when interpreted within the unit interval [0, 1], typically treating them as equivalent normalized or fractional quantities.
-
E.
apportionmentInterval
Indicates the time span or interval over which something (such as a quantity, cost, or resource) is allocated or distributed.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e6399d88190b2c3e781667666d4 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:12 a.m.