Triple

T4541995
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Metro E107554 entity
Predicate hasLine P35 FINISHED
Object Line 7
Line 7 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts across the city.
 E451280 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 7 | Statement: [Shenzhen Metro, hasLine, Line 7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 7
Context triple: [Shenzhen Metro, hasLine, Line 7]
  • A. Line 7
    Line 7 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • B. Line 7
    Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
  • C. Line 7
    Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
  • D. Line 7
    Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
  • E. Line 7
    Line 7 is a trolleybus route within Geneva’s public transport system that connects key districts of 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 7
Triple: [Shenzhen Metro, hasLine, Line 7]
Generated description
Line 7 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 7
Target entity description: Line 7 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts across the city.
  • A. Line 7
    Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
  • B. Line 7
    Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
  • C. Line 7
    Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
  • D. Line 7
    Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
  • E. Line 7
    Line 7 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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.