Triple
T22031563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toishan dialect |
E544099
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Enping |
—
|
NE NERFINISHED |
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: Enping | Statement: [Toishan dialect, spokenIn, Enping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enping Context triple: [Toishan dialect, spokenIn, Enping]
-
A.
Enping
chosen
Enping is a county-level city in Guangdong Province, China, known as part of the Sze Yup region and for its significant overseas Chinese diaspora.
-
B.
Wanning
Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
-
C.
Lingshui
Lingshui is a coastal county-level city in southeastern Hainan, China, known for its tropical climate, beaches, and growing tourism industry.
-
D.
Yunfu
Yunfu is a prefecture-level city in western Guangdong Province, China, known for its stone-processing industry and karst landscapes.
-
E.
Wenchang
Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127edd5b48190a9aeb2840105c181 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:24 p.m.