Triple

T4541993
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 5
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
E452470 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 5 | Statement: [Shenzhen Metro, hasLine, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Shenzhen Metro, hasLine, Line 5]
  • A. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • B. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • C. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • D. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • E. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across 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 5
Triple: [Shenzhen Metro, hasLine, Line 5]
Generated description
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
  • A. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • B. Line 5
    Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • C. Line 5
    Line 5 is a planned rapid transit route of the Ho Chi Minh City Metro system intended to serve as part of the city’s future urban rail network.
  • D. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • E. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs 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_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.