Triple

T530963
Position Surface form Disambiguated ID Type / Status
Subject Beijing Subway E12220 entity
Predicate hasLine P35 FINISHED
Object 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.
 E66117 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 10 | Statement: [Beijing Subway, hasLine, Line 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 10
Context triple: [Beijing Subway, hasLine, Line 10]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Line 5
    Line 5 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 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • 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 10
Triple: [Beijing Subway, hasLine, Line 10]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 10
Target entity description: 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.
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Line 5
    Line 5 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 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • 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.