Triple
T4843628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overtone |
E108236
|
entity |
| Predicate | numberingRule |
P20334
|
FINISHED |
| Object | First overtone corresponds to second harmonic in common usage |
—
|
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: First overtone corresponds to second harmonic in common usage | Statement: [Overtone, numberingRule, First overtone corresponds to second harmonic in common usage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberingRule Context triple: [Overtone, numberingRule, First overtone corresponds to second harmonic in common usage]
-
A.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
B.
standardNumberingScheme
chosen
Indicates that there is a specific, commonly accepted numbering system or convention being applied to identify or order the related entities.
-
C.
ruleNumber
Indicates that an entity is associated with a specific rule identified by its number within a set of rules.
-
D.
includesNumberingRange
Indicates that one entity contains or covers a specified contiguous range of numbers associated with another entity.
-
E.
countingRule
Indicates the rule or method used to count or quantify items, events, or entities in a given context.
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2375a4819098e16acb982c8fab |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.