Triple

T7949470
Position Surface form Disambiguated ID Type / Status
Subject Milano Cadorna station E184577 entity
Predicate hasMetroLine P17559 FINISHED
Object Line 1
Line 1 is a major Milan Metro line that serves key areas of the city, including Milano Cadorna station.
E704598 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: [Milano Cadorna station, hasMetroLine, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 1
Context triple: [Milano Cadorna station, hasMetroLine, 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 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.
  • C. Line 1
    Line 1 is the oldest and one of the busiest lines of the Mexico City Metro, running east–west across the city and serving many central, high-traffic stations.
  • D. Line 1
    Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
  • E. Line 1
    Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest 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 1
Triple: [Milano Cadorna station, hasMetroLine, Line 1]
Generated description
Line 1 is a major Milan Metro line that serves key areas of the city, including Milano Cadorna station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 1
Target entity description: Line 1 is a major Milan Metro line that serves key areas of the city, including Milano Cadorna station.
  • A. Line 1
    Line 1 is the first and main automated metro line of the Turin Metro system in Turin, Italy, connecting key areas of the city along an underground route.
  • B. Line 1
    Line 1 is one of the main lines of the Barcelona Metro rapid transit system, running on a largely east–west axis and serving several key districts of the city.
  • C. Line 1
    Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
  • D. Line 1
    Line 1 is the oldest and one of the busiest lines of the Paris Métro, running primarily east–west through central Paris and serving many major landmarks.
  • E. Line 1
    Line 1 is the first and main rapid transit line of the Seville Metro system in Seville, Spain, connecting key districts across the metropolitan area.
  • 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_69ca8292cba881908a64427b938dac47 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b2d09a4819097aa49e29a5426ec completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe03c7d308190aec1172415be995c completed March 31, 2026, 2:54 p.m.
NEDg Description generation batch_69cbe4383d0c819085e7c95e7b0be16e completed March 31, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69cc34a83cec81908aba7afbaea53449 completed March 31, 2026, 8:55 p.m.
Created at: March 30, 2026, 5:10 p.m.