Triple

T8077550
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Metro Line 1 E188529 entity
Predicate depot P14646 FINISHED
Object Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
 E710384 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: Meilong Depot | Statement: [Shanghai Metro Line 1, depot, Meilong Depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Meilong Depot
Context triple: [Shanghai Metro Line 1, depot, Meilong Depot]
  • A. Wanshengwei Depot
    Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
  • B. Daliao Depot
    Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
  • C. Tuqiao Depot
    Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
  • D. Sanyuanqiao depot
    Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
  • E. Xilang Depot
    Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
  • 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: Meilong Depot
Triple: [Shanghai Metro Line 1, depot, Meilong Depot]
Generated description
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Meilong Depot
Target entity description: Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
  • A. Wanshengwei Depot
    Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
  • B. Daliao Depot
    Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
  • C. Tuqiao Depot
    Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
  • D. Sanyuanqiao depot
    Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
  • E. Xilang Depot
    Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
  • 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_69ca82b50c708190863f661d438e68df completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a184488190b19ef7066f0f5057 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63f3f6848190a719b8a9605218ee completed April 1, 2026, 12:16 a.m.
NEDg Description generation batch_69cc651d340c819089306bac7110f57a completed April 1, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69cc666ecc04819092ee4cc035dde627 completed April 1, 2026, 12:27 a.m.
Created at: March 30, 2026, 5:28 p.m.