Triple
T1877832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern China |
E39183
|
entity |
| Predicate | hasLanguageGroup |
P3349
|
FINISHED |
| Object | Pinghua |
E185259
|
NE 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: Pinghua | Statement: [Southern China, hasLanguageGroup, Pinghua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pinghua Context triple: [Southern China, hasLanguageGroup, Pinghua]
-
A.
Pinghua
chosen
Pinghua is a Sinitic language variety spoken primarily in parts of Guangxi and neighboring regions in southern China, often considered distinct from both Cantonese and Mandarin.
-
B.
Zhizhong
Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
-
C.
Guanggu
Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
-
D.
Paihuano
Paihuano is a small town and commune in Chile’s Elqui Valley, known for its clear skies, pisco production, and astrotourism.
-
E.
Xinyu
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f79fbc819085c54f3189a552d9 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf59a5b48190bb4b47641681ebb7 |
completed | March 8, 2026, 8:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.