Triple
T8439717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wukang Road |
E199318
|
entity |
| Predicate | ChineseName |
P744
|
FINISHED |
| Object | 武康路 |
E199318
|
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: 武康路 | Statement: [Wukang Road, ChineseName, 武康路]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 武康路 Context triple: [Wukang Road, ChineseName, 武康路]
-
A.
Wukang Road
chosen
Wukang Road is a historic, tree-lined street in Shanghai known for its well-preserved early 20th-century architecture and cultural landmarks.
-
B.
Pingjiang Road
Pingjiang Road is a historic canal-side street in Suzhou famed for its well-preserved traditional architecture, stone bridges, and teahouses that showcase the charm of classical Jiangnan water-town life.
-
C.
Yuyuan Road
Yuyuan Road is a historic and culturally rich street in Shanghai known for its traditional architecture, local shops, and blend of old and modern urban life.
-
D.
Huashan Road
Huashan Road is a notable street in Shanghai’s former French Concession, known for its mix of historic architecture, embassies, universities, and cultural venues.
-
E.
Chengdu Road
Chengdu Road is a prominent thoroughfare in Taipei’s Ximending district, known for its dense concentration of shops, eateries, and entertainment venues.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe13708988190a534e38d8254c9bd |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d9140b48190ad0c493948a3de5e |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.