Triple
T4090137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 陳 |
E87685
|
entity |
| Predicate | cantonesePronunciationIPA |
P5704
|
FINISHED |
| Object | [tsʰɐn˨˩] |
—
|
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: [tsʰɐn˨˩] | Statement: [陳, cantonesePronunciationIPA, [tsʰɐn˨˩]]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cantonesePronunciationIPA Context triple: [陳, cantonesePronunciationIPA, [tsʰɐn˨˩]]
-
A.
cantoneseYaleForm
Indicates the written form of a term using the Yale romanization system for Cantonese pronunciation.
-
B.
ChinesePinyin
Indicates that one entity is the Chinese pinyin (romanized phonetic transcription) representation of another entity.
-
C.
hasIPA
chosen
Indicates that an entity is associated with a specific International Phonetic Alphabet (IPA) transcription representing its pronunciation.
-
D.
typeOfPronunciationDescribed
Indicates that one entity specifies or characterizes the kind or style of pronunciation associated with another entity.
-
E.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcab0a1c8190a1b0ca48ebc95b31 |
completed | March 9, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.