Triple

T9408909
Position Surface form Disambiguated ID Type / Status
Subject Tasqueña station E226656 entity
Predicate metroLine P848 FINISHED
Object Line 2
Line 2 is one of the main lines of the Mexico City Metro, running in a generally north–south direction and serving several key transit hubs across the city.
E100151 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: [Tasqueña station, metroLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Tasqueña station, metroLine, Line 2]
  • A. 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.
  • B. 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.
  • 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 planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
  • 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: [Tasqueña station, metroLine, Line 2]
Generated description
Line 2 is one of the main lines of the Mexico City Metro, running in a generally north–south direction and serving several key transit hubs 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 Mexico City Metro, running in a generally north–south direction and serving several key transit hubs across the city.
  • A. Line 2 chosen
    Line 2 is one of the principal lines of the Mexico City Metro system, running across key central and western areas of the city and serving as a major high-capacity transit corridor.
  • B. 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.
  • C. 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.
  • D. Line 2
    Line 2 is a major east–west rapid transit route of the Nanjing Metro system in Nanjing, China, connecting key urban districts and transportation hubs.
  • E. Line 2
    Line 2 is one of the main lines of the Milan Metro rapid transit system, connecting key districts across the city.
  • F. None of above.

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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd52547f0c81908ed4f53b9f05ebaa completed April 1, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107a5fcc081909a2d743e9673fe9e completed April 4, 2026, 12:44 p.m.
NEDg Description generation batch_69d1082f41b48190b8588bb986028f59 completed April 4, 2026, 12:46 p.m.
NED2 Entity disambiguation (via description) batch_69d108be82888190b0ec08119cd00b68 completed April 4, 2026, 12:49 p.m.
Created at: March 30, 2026, 7:47 p.m.