Triple
T8862897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 13 |
E210935
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Zhenru station
Zhenru station is an interchange station on the Shanghai Metro serving multiple lines in the Putuo District of Shanghai, China.
|
E849789
|
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: Zhenru station | Statement: [Shanghai Metro Line 13, hasStation, Zhenru station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhenru station Context triple: [Shanghai Metro Line 13, hasStation, Zhenru station]
-
A.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
-
B.
Shichahai station
Shichahai station is an underground metro stop on the Beijing Subway serving the historic Shichahai scenic area near central Beijing.
-
C.
Jishuitan station
Jishuitan station is a subway station in Beijing that serves the busy Line 2 loop near the city’s northern central area.
-
D.
Beitucheng station
Beitucheng station is an interchange station on the Beijing Subway that connects Line 8 with other key routes in the city's metro network.
-
E.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
- 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: Zhenru station Triple: [Shanghai Metro Line 13, hasStation, Zhenru station]
Generated description
Zhenru station is an interchange station on the Shanghai Metro serving multiple lines in the Putuo District of Shanghai, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zhenru station Target entity description: Zhenru station is an interchange station on the Shanghai Metro serving multiple lines in the Putuo District of Shanghai, China.
-
A.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
-
B.
Shichahai station
Shichahai station is an underground metro stop on the Beijing Subway serving the historic Shichahai scenic area near central Beijing.
-
C.
Jishuitan station
Jishuitan station is a subway station in Beijing that serves the busy Line 2 loop near the city’s northern central area.
-
D.
Beitucheng station
Beitucheng station is an interchange station on the Beijing Subway that connects Line 8 with other key routes in the city's metro network.
-
E.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc610263048190931bb2c3ac573a08 |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6523db338819088e2fadf346ad845 |
completed | April 8, 2026, 1:03 p.m. |
| NEDg | Description generation | batch_69d6561b8ad081908bed1bb0374a6e93 |
completed | April 8, 2026, 1:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d656ef9cb88190b88345a45fbeca1d |
completed | April 8, 2026, 1:23 p.m. |
Created at: March 30, 2026, 6:50 p.m.