Triple
T16652518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taipei Metro Bannan Line |
E404640
|
entity |
| Predicate | depot |
P14646
|
FINISHED |
| Object |
Tucheng Depot
Tucheng Depot is a maintenance and storage facility serving trains on Taipei's Bannan Line in New Taipei City, Taiwan.
|
E1226614
|
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: Tucheng Depot | Statement: [Taipei Metro Bannan Line, depot, Tucheng Depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tucheng Depot Context triple: [Taipei Metro Bannan Line, depot, Tucheng Depot]
-
A.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
B.
Zhujiajiao Depot
Zhujiajiao Depot is a maintenance and storage facility serving Shanghai Metro’s Line 17 near the historic town of Zhujiajiao in Qingpu District.
-
C.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Zhuxinzhuang depot
Zhuxinzhuang depot is a facility on the Beijing Subway network used for the storage, maintenance, and dispatch of trains serving Line 8.
- 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: Tucheng Depot Triple: [Taipei Metro Bannan Line, depot, Tucheng Depot]
Generated description
Tucheng Depot is a maintenance and storage facility serving trains on Taipei's Bannan Line in New Taipei City, Taiwan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tucheng Depot Target entity description: Tucheng Depot is a maintenance and storage facility serving trains on Taipei's Bannan Line in New Taipei City, Taiwan.
-
A.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
B.
Zhujiajiao Depot
Zhujiajiao Depot is a maintenance and storage facility serving Shanghai Metro’s Line 17 near the historic town of Zhujiajiao in Qingpu District.
-
C.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Zhuxinzhuang depot
Zhuxinzhuang depot is a facility on the Beijing Subway network used for the storage, maintenance, and dispatch of trains serving Line 8.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bf7ae7c81908b6807acd8f1669b |
completed | April 18, 2026, 12:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084c4c6a08190874264b2840fc70d |
completed | May 10, 2026, 1:14 p.m. |
| NEDg | Description generation | batch_6a00867b9314819080775dff976f93bd |
completed | May 10, 2026, 1:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00874646c081908d8a83dd8fd44941 |
completed | May 10, 2026, 1:25 p.m. |
Created at: April 10, 2026, 5:18 a.m.