Triple

T4541992
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 4
Line 4 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's major north–south corridors.
E451278 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 4 | Statement: [Shenzhen Metro, hasLine, Line 4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 4
Context triple: [Shenzhen Metro, hasLine, Line 4]
  • A. Line 4
    Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part of the city.
  • B. Line 4
    Line 4 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving key urban and suburban areas along its north–south corridor.
  • C. Line 4
    Line 4 is one of the main lines of the Tehran Metro rapid transit system, serving key east–west corridors across Iran’s capital city.
  • D. Line 4
    Line 4 is a circular rapid transit route of the Shanghai Metro system that loops around central districts and provides key transfer connections across the network.
  • E. Line 4
    Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
  • 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 4
Triple: [Shenzhen Metro, hasLine, Line 4]
Generated description
Line 4 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's major north–south corridors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 4
Target entity description: Line 4 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's major north–south corridors.
  • A. Line 4
    Line 4 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving key urban and suburban areas along its north–south corridor.
  • B. Line 4
    Line 4 is a major north–south rapid transit route in the Beijing Subway system, serving key commercial, residential, and university areas of the city.
  • C. Line 4
    Line 4 is a circular rapid transit route of the Shanghai Metro system that loops around central districts and provides key transfer connections across the network.
  • D. Line 4
    Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
  • E. Line 4
    Line 4 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
  • 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.