Triple
T453306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard Chinese |
E7177
|
entity |
| Predicate | primaryPhonologicalBasis |
P5210
|
FINISHED |
| Object | Beijing pronunciation |
—
|
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: Beijing pronunciation | Statement: [Standard Chinese, primaryPhonologicalBasis, Beijing pronunciation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPhonologicalBasis Context triple: [Standard Chinese, primaryPhonologicalBasis, Beijing pronunciation]
-
A.
hasPhonologicalType
Indicates that one entity is characterized by or classified as having a particular phonological type (e.g., in terms of sound structure or phonological category).
-
B.
hasStandardPronunciationBasedOn
chosen
Indicates that one entity’s standard or canonical pronunciation is determined or derived from another entity’s pronunciation.
-
C.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
-
D.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
E.
isPhonetic
Indicates that one entity represents the phonetic (sound-based) form or pronunciation of 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.