Triple
T11266927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 17 |
E266709
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Xuying Road
Xuying Road is a metro station in Shanghai, China, serving passengers on the city's Line 17.
|
E919707
|
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: Xuying Road | Statement: [Shanghai Metro Line 17, hasStation, Xuying Road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xuying Road Context triple: [Shanghai Metro Line 17, hasStation, Xuying Road]
-
A.
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.
-
B.
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.
-
C.
Huizhen Road
Huizhen Road is a metro station in Shanghai, China, serving as the southern terminus of the Pujiang Line.
-
D.
Linping Road
Linping Road is a station on Shanghai’s Metro system, serving passengers on Line 4 in the city’s urban rail network.
-
E.
Changle Road
Changle Road is a historic, tree-lined street in Shanghai known for its European-style architecture, boutiques, and cafés 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: Xuying Road Triple: [Shanghai Metro Line 17, hasStation, Xuying Road]
Generated description
Xuying Road is a metro station in Shanghai, China, serving passengers on the city's Line 17.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xuying Road Target entity description: Xuying Road is a metro station in Shanghai, China, serving passengers on the city's Line 17.
-
A.
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.
-
B.
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.
-
C.
Huizhen Road
Huizhen Road is a metro station in Shanghai, China, serving as the southern terminus of the Pujiang Line.
-
D.
Linping Road
Linping Road is a station on Shanghai’s Metro system, serving passengers on Line 4 in the city’s urban rail network.
-
E.
Changle Road
Changle Road is a historic, tree-lined street in Shanghai known for its European-style architecture, boutiques, and cafés 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94e5e3c8190a31995d55d20d7ed |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e542c5fdb88190968831279eaeea49 |
completed | April 19, 2026, 9:01 p.m. |
| NEDg | Description generation | batch_69e5474879088190990468d960b26739 |
completed | April 19, 2026, 9:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54eccdd3881908536ee3f9f4ef516 |
completed | April 19, 2026, 9:53 p.m. |
Created at: April 8, 2026, 9:31 p.m.