Triple
T453325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard Chinese |
E7177
|
entity |
| Predicate | numberOfTonesInCitationSystem |
P4432
|
FINISHED |
| Object | 4 lexical tones plus neutral 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: 4 lexical tones plus neutral tone | Statement: [Standard Chinese, numberOfTonesInCitationSystem, 4 lexical tones plus neutral tone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTonesInCitationSystem Context triple: [Standard Chinese, numberOfTonesInCitationSystem, 4 lexical tones plus neutral tone]
-
A.
representsNumberOfTones
chosen
Indicates that one entity specifies or encodes the number of tones associated with another entity.
-
B.
numberOfOrganPipes
Indicates the quantitative relationship specifying how many organ pipes are associated with a given organ or organ-related entity.
-
C.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
D.
numberOfTracks
Indicates the quantity of tracks associated with a given entity.
-
E.
typicalNotation
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef866e848190a5b700250ec56256 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede3187c8190a7ced078f0ec3476 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.