Triple
T2562544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guoyu |
E57273
|
entity |
| Predicate | numberOfTonesInStandard |
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: [Guoyu, numberOfTonesInStandard, 4 lexical tones plus neutral tone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTonesInStandard Context triple: [Guoyu, numberOfTonesInStandard, 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.
numberInInstrument
Indicates that an entity specifies the count or quantity of items contained within or associated with a particular instrument.
-
C.
numberOfOrganPipes
Indicates the quantitative relationship specifying how many organ pipes are associated with a given organ or organ-related entity.
-
D.
numberOfBells
Indicates the quantity of bells associated with or present in a given entity or context.
-
E.
numberOfTubes
Indicates the quantity of tubes associated with or contained by a given 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.