Triple
T10082260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 4 |
E213929
|
entity |
| Predicate | connectsStation |
P845
|
FINISHED |
| Object |
Linping Road
Linping Road is a station on Shanghai’s Metro system, serving passengers on Line 4 in the city’s urban rail network.
|
E852749
|
NE FINISHED |
How this triple was built (4 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: Linping Road | Statement: [Shanghai Metro Line 4, connectsStation, Linping Road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linping Road Context triple: [Shanghai Metro Line 4, connectsStation, Linping Road]
-
A.
Hangzhong Road
Hangzhong Road is a Shanghai Metro station that serves as a terminus on a branch of Line 10 in Shanghai, China.
-
B.
Lancun Road
Lancun Road is a Shanghai Metro interchange station serving multiple lines in the Pudong New Area of Shanghai, China.
-
C.
Changshou Road
Changshou Road is a major thoroughfare in Shanghai, China, known for its dense commercial activity and urban residential neighborhoods within the central city.
-
D.
Yishan Road
Yishan Road is a Shanghai Metro interchange station serving multiple lines in the Xuhui District of Shanghai, China.
-
E.
Dongping Road
Dongping Road is a historic, tree-lined street in Shanghai known for its European-style architecture, cafes, and cultural landmarks dating back to the city’s colonial era.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Linping Road Triple: [Shanghai Metro Line 4, connectsStation, Linping Road]
Generated description
Linping Road is a station on Shanghai’s Metro system, serving passengers on Line 4 in the city’s urban rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Linping Road Target entity description: Linping Road is a station on Shanghai’s Metro system, serving passengers on Line 4 in the city’s urban rail network.
-
A.
Hangzhong Road
Hangzhong Road is a Shanghai Metro station that serves as a terminus on a branch of Line 10 in Shanghai, China.
-
B.
Lancun Road
Lancun Road is a Shanghai Metro interchange station serving multiple lines in the Pudong New Area of Shanghai, China.
-
C.
Changshou Road
Changshou Road is a major thoroughfare in Shanghai, China, known for its dense commercial activity and urban residential neighborhoods within the central city.
-
D.
Yishan Road
Yishan Road is a Shanghai Metro interchange station serving multiple lines in the Xuhui District of Shanghai, China.
-
E.
Dongping Road
Dongping Road is a historic, tree-lined street in Shanghai known for its European-style architecture, cafes, and cultural landmarks dating back to the city’s colonial era.
- F. None of above. chosen
Provenance (5 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd03482d481908b03d35dc2d16395 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f6ca9ac88190ac5f0a25954a2606 |
completed | April 9, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69d6fcaa16788190a4c7ef79a78febc6 |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd6d705c81908e469068937a79b3 |
completed | April 9, 2026, 1:14 a.m. |
Created at: March 30, 2026, 9 p.m.