Triple

T4541990
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 2
Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across the city.
E451277 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 2 | Statement: [Shenzhen Metro, hasLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Shenzhen Metro, hasLine, Line 2]
  • A. Line 2
    Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
  • B. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • C. Line 2
    Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
  • D. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • E. Line 2
    Line 2 is a planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
  • 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 2
Triple: [Shenzhen Metro, hasLine, Line 2]
Generated description
Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 2
Target entity description: Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across the city.
  • A. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • B. Line 2
    Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
  • C. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • D. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west across the city.
  • E. Line 2
    Line 2 is one of the principal lines of the Mexico City Metro system, running across key central and western areas of the city and serving as a major high-capacity transit corridor.
  • 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.