Triple

T9547227
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Metro Line 3 E230322 entity
Predicate depot P14646 FINISHED
Object Jiangwan Town depot
Jiangwan Town depot is a maintenance and storage facility serving Shanghai Metro Line 3 in Shanghai, China.
 E805274 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: Jiangwan Town depot | Statement: [Shanghai Metro Line 3, depot, Jiangwan Town depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jiangwan Town depot
Context triple: [Shanghai Metro Line 3, depot, Jiangwan Town depot]
  • A. Xilang Depot
    Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
  • B. Wanshengwei Depot
    Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
  • C. Sanyuanqiao depot
    Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
  • D. Meilong Depot
    Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
  • E. Daliao Depot
    Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
  • 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: Jiangwan Town depot
Triple: [Shanghai Metro Line 3, depot, Jiangwan Town depot]
Generated description
Jiangwan Town depot is a maintenance and storage facility serving Shanghai Metro Line 3 in Shanghai, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jiangwan Town depot
Target entity description: Jiangwan Town depot is a maintenance and storage facility serving Shanghai Metro Line 3 in Shanghai, China.
  • A. Xilang Depot
    Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
  • B. Wanshengwei Depot
    Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
  • C. Sanyuanqiao depot
    Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
  • D. Meilong Depot
    Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
  • E. Daliao Depot
    Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9904732c8190ab60ecc47c995cbe completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c747e608190b2fa470324fff454 completed April 4, 2026, 5:37 p.m.
NEDg Description generation batch_69d14cfcfc6c8190a39f4db25ffa160e completed April 4, 2026, 5:40 p.m.
NED2 Entity disambiguation (via description) batch_69d14d5dad98819089c49afd3d097c1f completed April 4, 2026, 5:41 p.m.
Created at: March 30, 2026, 8:02 p.m.