Triple
T17006443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chàhn |
E412582
|
entity |
| Predicate | toneMarking |
P67250
|
FINISHED |
| Object | low falling tone in Yale romanization |
—
|
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: low falling tone in Yale romanization | Statement: [Chàhn, toneMarking, low falling tone in Yale romanization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneMarking Context triple: [Chàhn, toneMarking, low falling tone in Yale romanization]
-
A.
toneMarkFunction
Indicates a function or role that assigns, modifies, or interprets tone marks in a tonal or phonetic system.
-
B.
marksTones
Indicates that one entity applies or denotes tonal markings or distinctions on another entity, such as in language or notation.
-
C.
usesToneMarks
chosen
Indicates that one entity applies or includes diacritical tone marks in the representation or transcription of another entity (such as text, language, or symbols).
-
D.
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.
-
E.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d3831268819089286053a5acf653 |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.