Triple

T273856
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou E5203 entity
Predicate hasMetroSystem P522 FINISHED
Object Guangzhou Metro
Guangzhou Metro is the rapid transit system serving Guangzhou, China, forming one of the country’s largest and busiest urban rail networks.
E35677 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: Guangzhou Metro | Statement: [Guangzhou, hasMetroSystem, Guangzhou Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangzhou Metro
Context triple: [Guangzhou, hasMetroSystem, Guangzhou Metro]
  • A. Wuhan Metro
    Wuhan Metro is the rapid transit system serving the city of Wuhan, China, providing urban rail transportation across its major districts.
  • B. Beijing Subway
    The Beijing Subway is one of the world’s largest and busiest rapid transit systems, forming the backbone of public transportation in China’s capital city.
  • C. Osaka Metro
    Osaka Metro is the rapid transit network serving Japan’s city of Osaka and its surrounding urban area.
  • D. Guangzhou
    Guangzhou is a major port city in southern China and the capital of Guangdong Province, known as a key commercial and manufacturing hub in the Pearl River Delta.
  • E. Wuchang Railway Station
    Wuchang Railway Station is one of the main passenger rail hubs in Wuhan, China, serving as a key node for regional and long-distance train services.
  • 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: Guangzhou Metro
Triple: [Guangzhou, hasMetroSystem, Guangzhou Metro]
Generated description
Guangzhou Metro is the rapid transit system serving Guangzhou, China, forming one of the country’s largest and busiest urban rail networks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Guangzhou Metro
Target entity description: Guangzhou Metro is the rapid transit system serving Guangzhou, China, forming one of the country’s largest and busiest urban rail networks.
  • A. Wuhan Metro
    Wuhan Metro is the rapid transit system serving the city of Wuhan, China, providing urban rail transportation across its major districts.
  • B. Beijing Subway
    The Beijing Subway is one of the world’s largest and busiest rapid transit systems, forming the backbone of public transportation in China’s capital city.
  • C. Osaka Metro
    Osaka Metro is the rapid transit network serving Japan’s city of Osaka and its surrounding urban area.
  • D. Guangzhou
    Guangzhou is a major port city in southern China and the capital of Guangdong Province, known as a key commercial and manufacturing hub in the Pearl River Delta.
  • E. Wuchang Railway Station
    Wuchang Railway Station is one of the main passenger rail hubs in Wuhan, China, serving as a key node for regional and long-distance train services.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25dd0a99c819089968a5400c58c5f completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3914eba9081908cdef8b719c9b20b completed March 1, 2026, 1:07 a.m.
NEDg Description generation batch_69a391888bbc81908d86e3a1f15cb84e completed March 1, 2026, 1:08 a.m.
NED2 Entity disambiguation (via description) batch_69a3921fc8c8819084d2dab21012e53a completed March 1, 2026, 1:10 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.