Triple

T7949471
Position Surface form Disambiguated ID Type / Status
Subject Milano Cadorna station E184577 entity
Predicate hasMetroLine P17559 FINISHED
Object Line 2
Line 2 is one of the main lines of the Milan Metro rapid transit system, connecting key districts across the city.
E704599 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 2 | Statement: [Milano Cadorna station, hasMetroLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Milano Cadorna station, hasMetroLine, Line 2]
  • A. 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.
  • B. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • C. Line 2
    Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
  • D. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • E. Line 2
    Line 2 is a major circular line of the Seoul Metropolitan Subway system, known for being one of the busiest and most important routes in the network.
  • 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 2
Triple: [Milano Cadorna station, hasMetroLine, Line 2]
Generated description
Line 2 is one of the main lines of the Milan Metro rapid transit system, connecting key districts across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 2
Target entity description: Line 2 is one of the main lines of the Milan Metro rapid transit system, connecting key districts across the city.
  • A. Line 2
    Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
  • B. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • C. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • D. Line 2
    Line 2 is a major rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
  • E. Line 2
    Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across 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_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.