Triple
T2464157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton |
E55203
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Kuang-chou |
E268174
|
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: Kuang-chou | Statement: [Canton, hasAlternativeName, Kuang-chou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuang-chou Context triple: [Canton, hasAlternativeName, Kuang-chou]
-
A.
Kwang-chou
chosen
Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
-
B.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
C.
Dadu
Dadu was the Yuan dynasty capital city established by Kublai Khan on the site of present-day Beijing, serving as the political and cultural center of his empire.
-
D.
Qibao
Qibao is an ancient water town and popular tourist area in Shanghai, known for its historic streets, canals, and traditional architecture.
-
E.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd12059788190a6493f64bb725aed |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1799b530819095d828c9d4a9dc9c |
completed | March 9, 2026, 6:55 p.m. |
Created at: March 6, 2026, 9:44 p.m.