Triple

T530964
Position Surface form Disambiguated ID Type / Status
Subject Beijing Subway E12220 entity
Predicate hasLine P35 FINISHED
Object 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.
 E66476 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: [Beijing Subway, hasLine, Line 13]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 13
Context triple: [Beijing Subway, hasLine, Line 13]
  • A. Line 10
    Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
  • B. 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.
  • C. Line 8
    Line 8 is a route of Mexico City’s Metrobús bus rapid transit system, serving key corridors with dedicated lanes and station platforms.
  • D. 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.
  • E. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • 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: [Beijing Subway, hasLine, Line 13]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 13
Target entity description: 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.
  • A. Line 10
    Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
  • B. 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.
  • C. Line 8
    Line 8 is a route of Mexico City’s Metrobús bus rapid transit system, serving key corridors with dedicated lanes and station platforms.
  • D. 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.
  • E. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a494dda58c8190870305056838a2b2 completed March 1, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b8add810819095f071caca108e10 completed March 1, 2026, 10:07 p.m.
NEDg Description generation batch_69a4b9bb6c30819088d4d3cfab10408c completed March 1, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69a4ba8630508190b6ba32ad0aef2cd2 completed March 1, 2026, 10:15 p.m.
Created at: March 1, 2026, 7:32 p.m.