Triple
T29125308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liúyáng |
E738208
|
entity |
| Predicate | representsToneOnSyllableLiu |
P86505
|
FINISHED |
| Object | second 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: second tone | Statement: [Liúyáng, representsToneOnSyllableLiu, second tone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsToneOnSyllableLiu Context triple: [Liúyáng, representsToneOnSyllableLiu, second tone]
-
A.
mandarinTone
Indicates the specific tonal pattern in Mandarin Chinese with which an entity (such as a syllable or word) is pronounced.
-
B.
firstSyllableTone
Indicates that the relationship specifies the tonal value assigned to the first syllable of a word or expression.
-
C.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
D.
secondSyllableTone
chosen
Indicates that the relationship specifies the tonal value or pitch pattern of the second syllable in a word or utterance.
-
E.
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.
- 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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 28, 2026, 11:28 a.m.