Triple
T6177532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Plains Mandarin |
E137856
|
entity |
| Predicate | hasToneSystem |
P12025
|
FINISHED |
| Object | four lexical tones in most varieties |
—
|
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: four lexical tones in most varieties | Statement: [Central Plains Mandarin, hasToneSystem, four lexical tones in most varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToneSystem Context triple: [Central Plains Mandarin, hasToneSystem, four lexical tones in most varieties]
-
A.
hasPhonemicTone
chosen
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
B.
usesMusicalSystem
Indicates that one entity employs or operates according to a particular musical system, framework, or set of musical rules.
-
C.
tonalCharacteristic
Indicates the specific quality or character of a sound’s tone, such as its color, texture, or expressive nuance, in relation to an entity.
-
D.
hasEndingTone
Indicates that something concludes with a particular tone, mood, or intonational quality.
-
E.
marksTones
Indicates that one entity applies or denotes tonal markings or distinctions on another entity, such as in language or notation.
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dc87bc48190834042d9c41d5b86 |
completed | March 22, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.