Triple

T4541999
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 11
Line 11 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, providing high-speed urban and airport rail service across key districts.
E452472 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 11 | Statement: [Shenzhen Metro, hasLine, Line 11]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 11
Context triple: [Shenzhen Metro, hasLine, Line 11]
  • A. Line 11
    Line 11 is a short, automated light metro line in the Barcelona Metro network that serves the hilly northern suburbs of the city.
  • B. Line 11
    Line 11 is a major Shanghai Metro route known for its long cross-city alignment connecting suburban areas with central Shanghai and serving key commercial and residential districts.
  • C. Line 10
    Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
  • D. Line 10
    Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
  • E. Line 10
    Line 10 is a trolleybus route within Geneva’s public transport system that connects key districts and suburbs of 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 11
Triple: [Shenzhen Metro, hasLine, Line 11]
Generated description
Line 11 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, providing high-speed urban and airport rail service across key districts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 11
Target entity description: Line 11 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, providing high-speed urban and airport rail service across key districts.
  • A. Line 11
    Line 11 is a major Shanghai Metro route known for its long cross-city alignment connecting suburban areas with central Shanghai and serving key commercial and residential districts.
  • B. Line 11
    Line 11 is a short, automated light metro line in the Barcelona Metro network that serves the hilly northern suburbs of the city.
  • C. Line 10
    Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
  • D. Line 10
    Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
  • E. Line 10
    Line 10 is a major Shanghai Metro route known for serving central districts and key hubs such as Hongqiao Transportation Hub and the city’s historic and commercial areas.
  • 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_69bd43f922788190b7edfa294e39b178 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d219d88190a67ada845323d7fb completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc55ae8248190acda4f10eb5ce2e7 completed March 20, 2026, 10:08 p.m.
NEDg Description generation batch_69bdc758f0288190ad57ec8ef5786c66 completed March 20, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69bdc7d126fc819094a97fe155d267dd completed March 20, 2026, 10:18 p.m.
Created at: March 20, 2026, 1:04 p.m.