Triple

T4541998
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 10
Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
 E451281 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 10 | Statement: [Shenzhen Metro, hasLine, Line 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 10
Context triple: [Shenzhen Metro, hasLine, Line 10]
  • A. 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.
  • B. 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.
  • C. Line 10
    Line 10 is a trolleybus route within Geneva’s public transport system that connects key districts and suburbs of the city.
  • D. 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.
  • E. 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.
  • 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 10
Triple: [Shenzhen Metro, hasLine, Line 10]
Generated description
Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 10
Target entity description: Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
  • A. 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.
  • B. 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.
  • C. Line 10
    Line 10 is a trolleybus route within Geneva’s public transport system that connects key districts and suburbs of the city.
  • D. 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.
  • E. 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.
  • 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_69bdb926f2608190bdc6379e81358c38 completed March 20, 2026, 9:16 p.m.
NEDg Description generation batch_69bdbe0b6aa88190b6e99e4be1b27935 completed March 20, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69bdbe5eda748190b6d83d5f2c73cff5 completed March 20, 2026, 9:38 p.m.
Created at: March 20, 2026, 1:04 p.m.