Triple

T8949107
Position Surface form Disambiguated ID Type / Status
Subject Chongqing Metro E213296 entity
Predicate hasLine P35 FINISHED
Object Line 9
Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
 E768294 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: Line 9 | Statement: [Chongqing Metro, hasLine, Line 9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 9
Context triple: [Chongqing Metro, hasLine, Line 9]
  • A. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • B. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • C. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • D. Line 9
    Line 9 is a major Barcelona Metro line designed as a long, partially automated route connecting key suburban and airport areas with the wider metropolitan network.
  • E. Line 9
    Line 9 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts in 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: Line 9
Triple: [Chongqing Metro, hasLine, Line 9]
Generated description
Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 9
Target entity description: Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
  • A. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • B. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • C. Line 9
    Line 9 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts in the city.
  • D. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • E. Line 9
    Line 9 is a rapid transit route within the STC Metro system, serving as one of its numbered urban rail lines.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6709c7a48190ab503083a1d6a29f completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc206550c8190abf016f25b14fa64 completed April 3, 2026, 1:35 p.m.
NEDg Description generation batch_69cfc3f170a08190a2cab07eb280ee3b completed April 3, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_69cfc476204481909f0baaf400483f33 completed April 3, 2026, 1:45 p.m.
Created at: March 30, 2026, 6:59 p.m.