Triple
T22324420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 第二次上海事変 |
E551866
|
entity |
| Predicate | 主な戦場 |
P146580
|
FINISHED |
| Object | 宝山 |
—
|
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: 宝山 | Statement: [第二次上海事変, 主な戦場, 宝山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 宝山 Context triple: [第二次上海事変, 主な戦場, 宝山]
-
A.
松江市
松江市 is the capital city of Shimane Prefecture in Japan, known for its historic Matsue Castle, scenic lakes, and traditional cultural atmosphere.
-
B.
Baoshan District
chosen
Baoshan District is a northern suburban district of Shanghai known for its industrial base, port facilities, and growing residential and educational areas.
-
C.
卢湾区
卢湾区 was a former central district of Shanghai, China, known for its historic architecture, commercial streets, and role as part of the city’s traditional urban core before being merged into Huangpu District.
-
D.
Baoshan
Baoshan is a prefecture-level city in southwestern China known for its mountainous landscapes, border trade, and location along historical routes connecting Yunnan to Myanmar.
-
E.
Wujiang District
Wujiang District is a suburban district of Suzhou in Jiangsu Province, China, known for its historic water towns and rapidly developing economy.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15767425481909547bfe294fe06de |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:42 p.m.