Triple

T13140049
Position Surface form Disambiguated ID Type / Status
Subject Shijiazhuang Metro E312187 entity
Predicate hasLine P35 FINISHED
Object Line 3
Line 3 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
E1026107 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 3 | Statement: [Shijiazhuang Metro, hasLine, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 3
Context triple: [Shijiazhuang Metro, hasLine, Line 3]
  • A. Line 3
    Line 3 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 3
    Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
  • C. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • D. Line 3
    Line 3 is a future rapid transit route of the Seville Metro intended to extend and improve the city’s urban rail network.
  • E. Line 3
    Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
  • 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 3
Triple: [Shijiazhuang Metro, hasLine, Line 3]
Generated description
Line 3 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 3
Target entity description: Line 3 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
  • A. Line 3
    Line 3 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key urban districts along a major north–south corridor.
  • B. Line 3
    Line 3 is a rapid transit route of the Nanjing Metro system in Nanjing, China, serving as one of the city's main north–south subway lines.
  • C. Line 3
    Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
  • D. Line 3
    Line 3 is a major rapid transit route of the STC Metro system, serving key districts along its corridor.
  • E. Line 3
    Line 3 is a major rapid transit line of the Chongqing Metro system in Chongqing, China, known for its extensive elevated monorail route that connects key urban and suburban areas.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981b84f1081908b9e2d54a64d4c2d completed April 10, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5d809948190aced5ce377402463 completed May 3, 2026, 7:14 a.m.
NEDg Description generation batch_69f6f6e10f2481909b405169dd7e5cf9 completed May 3, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69f6f73b301881909d792dfebd2e468f completed May 3, 2026, 7:20 a.m.
Created at: April 9, 2026, 9:09 p.m.