Triple
T16106408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meizhou Mazu Temple |
E390748
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Fujian |
E41238
|
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: Fujian | Statement: [Meizhou Mazu Temple, locatedIn, Fujian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fujian Context triple: [Meizhou Mazu Temple, locatedIn, Fujian]
-
A.
Fujian
chosen
Fujian is a coastal province in southeastern China known for its significant role in Chinese migration, distinctive Min culture and dialects, and historic maritime trade.
-
B.
Jianxi
Jianxi was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
-
C.
Inland Fujian
Inland Fujian is the mountainous, landlocked interior region of China’s Fujian province, characterized by forested hills, river valleys, and relatively less coastal development.
-
D.
Kansu
Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
-
E.
Guangdong Province
Guangdong Province is a populous and economically vital coastal region in southern China, known for major cities like Guangzhou and Shenzhen and its role as a manufacturing and trade hub.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6d81d081909e1315f4dbfd7369 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00077efdf48190ac26f433f6b17dbe |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5 a.m.