Triple

T4542002
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 14
Line 14 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as part of the city's expanding urban rail network.
 E458986 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 14 | Statement: [Shenzhen Metro, hasLine, Line 14]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 14
Context triple: [Shenzhen Metro, hasLine, Line 14]
  • A. Line 14
    Line 14 is a major rapid transit line of the Beijing Subway system that serves multiple key residential and commercial districts across the city.
  • B. Line 14
    Line 14 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving suburban and outlying districts with high-speed, longer-distance urban rail service.
  • C. Line 14
    Line 14 is a rapid transit line of the Shanghai Metro system that serves as one of the city's major east–west corridors.
  • D. Line 14
    Line 14 is a fully automated, high-capacity line of the Paris Métro known for its modern trains and role in relieving congestion on central routes.
  • E. Line 13
    Line 13 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
  • 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 14
Triple: [Shenzhen Metro, hasLine, Line 14]
Generated description
Line 14 is a rapid transit line of the Shenzhen Metro system in Shenzhen, 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 14
Target entity description: Line 14 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as part of the city's expanding urban rail network.
  • A. Line 14
    Line 14 is a major rapid transit line of the Beijing Subway system that serves multiple key residential and commercial districts across the city.
  • B. Line 14
    Line 14 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving suburban and outlying districts with high-speed, longer-distance urban rail service.
  • C. Line 14
    Line 14 is a rapid transit line of the Shanghai Metro system that serves as one of the city's major east–west corridors.
  • D. Line 14
    Line 14 is a fully automated, high-capacity line of the Paris Métro known for its modern trains and role in relieving congestion on central routes.
  • E. Line 13
    Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • 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_69bdfa1681708190ae4dc66e8734e5a1 completed March 21, 2026, 1:53 a.m.
NEDg Description generation batch_69bdfb5502c48190b7679941b83e6e0c completed March 21, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69bdff53680c8190a62aace0f0c9f3b3 completed March 21, 2026, 2:15 a.m.
Created at: March 20, 2026, 1:04 p.m.