Triple

T1650411
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Metro E35677 entity
Predicate hasLine P35 FINISHED
Object 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.
 E187938 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: [Guangzhou Metro, hasLine, Line 14]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 14
Context triple: [Guangzhou 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 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • C. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • D. Line 15
    Line 15 is a rapid transit line of the Beijing Subway system serving northern parts of the city with both urban and suburban stations.
  • E. Line 16
    Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
  • 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: [Guangzhou Metro, hasLine, Line 14]
Generated description
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.
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 Guangzhou Metro system in Guangzhou, China, serving suburban and outlying districts with high-speed, longer-distance urban rail service.
  • 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 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • C. Line 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • D. Line 15
    Line 15 is a rapid transit line of the Beijing Subway system serving northern parts of the city with both urban and suburban stations.
  • E. Line 16
    Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a66b58c819082d38ef1c805cf44 completed March 5, 2026, 4:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad681db3408190a3b469e319486419 completed March 8, 2026, 12:14 p.m.
NEDg Description generation batch_69ad692a4078819080c3a89166917081 completed March 8, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_69ad698929f88190af97fc915d29a5b5 completed March 8, 2026, 12:20 p.m.
Created at: March 4, 2026, 7:29 p.m.