Triple

T1768701
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Metro E38822 entity
Predicate hasLine P35 FINISHED
Object Line 13
Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
 E205615 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 13 | Statement: [Shanghai Metro, hasLine, Line 13]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 13
Context triple: [Shanghai Metro, hasLine, Line 13]
  • A. 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.
  • B. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • C. 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.
  • D. 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.
  • E. Line 12
    Line 12 is a rapid transit line of the Shanghai Metro system that runs east–west across the city, connecting several key commercial and residential districts.
  • 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 13
Triple: [Shanghai Metro, hasLine, Line 13]
Generated description
Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 13
Target entity description: Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • A. 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.
  • B. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • C. 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.
  • D. 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.
  • E. Line 12
    Line 12 is a rapid transit line of the Shanghai Metro system that runs east–west across the city, connecting several key commercial and residential districts.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648d9f2c8190aca4884648a69eb0 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9a14a18819090b83b3d10304c74 completed March 8, 2026, 7:10 p.m.
NEDg Description generation batch_69adcaed1f788190b14c3e2d2c3036d9 completed March 8, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69adcbee97e88190adc1315c0a5013ab completed March 8, 2026, 7:20 p.m.
Created at: March 4, 2026, 7:31 p.m.