Triple
T21943049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sze Yup region |
E541868
|
entity |
| Predicate | hasNameInChinese |
P4878
|
FINISHED |
| Object | 四邑 |
—
|
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: 四邑 | Statement: [Sze Yup region, hasNameInChinese, 四邑]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 四邑 Context triple: [Sze Yup region, hasNameInChinese, 四邑]
-
A.
台山市
台山市是中国广东省江门市下辖的一座沿海县级市，以侨乡文化、海岛风光和碉楼建筑而闻名。
-
B.
荔湾区
荔湾区 is a historic urban district of Guangzhou, China, known for its traditional Lingnan architecture, cultural heritage sites, and vibrant commercial streets.
-
C.
Shunde District
Shunde District is a prosperous urban district in Foshan, Guangdong, China, known for its manufacturing industry, Cantonese cuisine, and cultural attractions.
-
D.
新會
chosen
新會 is a historic town and district-level area in Jiangmen, Guangdong, China, known as a traditional emigration center and part of the culturally rich Sze Yup region.
-
E.
海珠区
海珠区 is a central urban district of Guangzhou in Guangdong Province, China, known for its dense residential areas, commercial centers, and role in the city’s economic and cultural life.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.