Triple
T8906440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 外滩 |
E212071
|
entity |
| Predicate | 位于 |
P40
|
FINISHED |
| Object | 黄浦区 |
E188528
|
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: 黄浦区 | Statement: [外滩, 位于, 黄浦区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 黄浦区 Context triple: [外滩, 位于, 黄浦区]
-
A.
Changning District
Changning District is a central urban district of Shanghai, China, known for its residential neighborhoods, commercial centers, and the city’s main international airport, Hongqiao.
-
B.
Xuhui District
Xuhui District is a central urban district of Shanghai, China, known for its historic architecture, cultural institutions, and major commercial and educational hubs.
-
C.
Yangpu District
Yangpu District is an urban district in northeastern Shanghai known for its universities, technology hubs, and historic industrial waterfront along the Huangpu River.
-
D.
Huangpu District, Shanghai
chosen
Huangpu District, Shanghai is the historic and commercial heart of central Shanghai, encompassing major landmarks such as the Bund and key shopping and business streets.
-
E.
Baoshan District
Baoshan District is a northern suburban district of Shanghai known for its industrial base, port facilities, and growing residential and educational areas.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c51d6c819098dc33a480dfd462 |
completed | April 1, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba2cb5e48190813e9c08198149b0 |
completed | April 3, 2026, 1:01 p.m. |
Created at: March 30, 2026, 6:55 p.m.