Triple

T3515772
Position Surface form Disambiguated ID Type / Status
Subject Turin Metro E74302 entity
Predicate line P1293 FINISHED
Object 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.
E365560 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: [Turin Metro, line, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 1
Context triple: [Turin Metro, line, 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 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.
  • 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 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.
  • E. Line 1
    Line 1 is the first operational corridor of the Mumbai Monorail system, serving as a key elevated transit route in Mumbai, India.
  • 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: [Turin Metro, line, Line 1]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 1
Target entity description: 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.
  • A. 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.
  • B. Line 1
    Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
  • C. Line 1
    Line 1 is a major east–west rapid transit route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • D. 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.
  • E. 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.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc30362c81908ca7497a6a935cc6 completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e7a5ab08190971c9dfd6550eb2d completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37ff7b1c8819085b16ea9eb9175eb completed March 13, 2026, 3:09 a.m.
NED2 Entity disambiguation (via description) batch_69b3808903e481908d312766e126204f completed March 13, 2026, 3:12 a.m.
Created at: March 8, 2026, 3:19 p.m.