Triple

T8735797
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Metro Line 9 E207378 entity
Predicate depot P14646 FINISHED
Object Caolu Depot
Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
 E753262 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: Caolu Depot | Statement: [Shanghai Metro Line 9, depot, Caolu Depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Caolu Depot
Context triple: [Shanghai Metro Line 9, depot, Caolu Depot]
  • A. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • B. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • C. Sharston depot
    Sharston depot is a bus operating and maintenance facility in the Sharston area of Manchester used by Stagecoach Manchester for its local services.
  • D. Munyang Depot
    Munyang Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
  • E. Morden depot
    Morden depot is a major London Underground maintenance and stabling facility serving the Northern line at its southern end.
  • 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: Caolu Depot
Triple: [Shanghai Metro Line 9, depot, Caolu Depot]
Generated description
Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Caolu Depot
Target entity description: Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
  • A. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • B. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • C. Sharston depot
    Sharston depot is a bus operating and maintenance facility in the Sharston area of Manchester used by Stagecoach Manchester for its local services.
  • D. Munyang Depot
    Munyang Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
  • E. Morden depot
    Morden depot is a major London Underground maintenance and stabling facility serving the Northern line at its southern end.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d44275881909f7eb40b24180294 completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf293a6a3c8190b37738d222b9212f completed April 3, 2026, 2:43 a.m.
NEDg Description generation batch_69cf2bd4f50c8190bad328e82d299ae0 completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2cbf60808190a006ee4fb26cde41 completed April 3, 2026, 2:58 a.m.
Created at: March 30, 2026, 6:37 p.m.