Triple
T22031592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toishan dialect |
E544099
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Hoisanese |
—
|
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: Hoisanese | Statement: [Toishan dialect, alternativeName, Hoisanese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoisanese Context triple: [Toishan dialect, alternativeName, Hoisanese]
-
A.
Hoisanese
chosen
Hoisanese is a Yue Chinese dialect spoken primarily by people from Taishan in Guangdong, China, and their overseas communities.
-
B.
Hoisan
Hoisan is an older romanization of Taishan, a county-level city in Guangdong, China, historically known for its large overseas Chinese diaspora.
-
C.
Nagamese
Nagamese is a widely used Assamese-based creole lingua franca in Nagaland, India, facilitating communication among diverse Naga ethnic groups.
-
D.
Bugis
The Bugis are a seafaring Austronesian ethnic group from South Sulawesi, Indonesia, known historically as skilled sailors, traders, and navigators.
-
E.
Bugis
Bugis is a vibrant commercial and cultural district in Singapore known for its shopping streets, markets, and nightlife.
- 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.