Triple
T21943212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qieyun |
E541871
|
entity |
| Predicate | hasToneCategories |
P67251
|
FINISHED |
| Object | level tone |
—
|
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: level tone | Statement: [Qieyun, hasToneCategories, level tone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToneCategories Context triple: [Qieyun, hasToneCategories, level tone]
-
A.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
B.
supportsTone
Indicates that one entity is compatible with, enables, or can correctly handle a specified tone or tonal characteristic of another entity.
-
C.
marksTones
chosen
Indicates that one entity applies or denotes tonal markings or distinctions on another entity, such as in language or notation.
-
D.
toneCount
Indicates the number of distinct tones or tonal elements associated with an entity or expression.
-
E.
inTonality
Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:56 p.m.