Triple
T22431876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siyi Yue |
E554518
|
entity |
| Predicate | hasDialectRegion |
P48907
|
FINISHED |
| Object | Xinhui |
—
|
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: Xinhui | Statement: [Siyi Yue, hasDialectRegion, Xinhui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinhui Context triple: [Siyi Yue, hasDialectRegion, Xinhui]
-
A.
Xinhui
chosen
Xinhui is a district in Jiangmen, Guangdong Province, China, historically known as a significant hometown of overseas Chinese and part of the Pearl River Delta region.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Fenghua
Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
-
D.
Changshou
Changshou was a Chinese imperial era name used during the reign of Empress Wu Zetian in the Tang dynasty.
-
E.
Changxun
Changxun was the given name of Zhu Changxun, a Ming dynasty imperial prince and son of the Wanli Emperor.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a32139481909baaf9275f5e0257 |
completed | April 29, 2026, 1:09 a.m. |
Created at: April 16, 2026, 8:47 p.m.