Triple

T530955
Position Surface form Disambiguated ID Type / Status
Subject Beijing Subway E12220 entity
Predicate hasLine P35 FINISHED
Object 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.
 E66114 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 1 | Statement: [Beijing Subway, hasLine, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 1
Context triple: [Beijing Subway, hasLine, Line 1]
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • B. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west across the city.
  • C. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • D. Line 2
    Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
  • E. 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.
  • 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 1
Triple: [Beijing Subway, hasLine, Line 1]
Generated description
Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 1
Target entity description: Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • B. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west across the city.
  • C. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • D. Line 2
    Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
  • E. 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.
  • 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_69a4b5dabbe88190acf66bd30bc6312d completed March 1, 2026, 9:55 p.m.
NEDg Description generation batch_69a4b64487bc8190b879ddedc1585a04 completed March 1, 2026, 9:57 p.m.
NED2 Entity disambiguation (via description) batch_69a4b6ca3398819094bfbac0ba7a9c66 completed March 1, 2026, 9:59 p.m.
Created at: March 1, 2026, 7:32 p.m.