Triple

T10754782
Position Surface form Disambiguated ID Type / Status
Subject Rouen tramway E253661 entity
Predicate hasLine P35 FINISHED
Object Line T1
Line T1 is a principal route of the Rouen tramway system in France, providing light rail transit service through key areas of the city and its suburbs.
 E884439 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 T1 | Statement: [Rouen tramway, hasLine, Line T1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line T1
Context triple: [Rouen tramway, hasLine, Line T1]
  • A. Line L
    Line L is a cable car line of the Medellín Metro system that serves hillside neighborhoods by connecting them to the main urban transit network.
  • B. Line 1
    Line 1 is the first operational corridor of the Mumbai Monorail system, serving as a key elevated transit route in Mumbai, India.
  • C. Line 1
    Line 1 is a primary Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
  • D. Line 1
    Line 1 is a major Milan Metro line that serves key areas of the city, including Milano Cadorna station.
  • 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
  • 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 T1
Triple: [Rouen tramway, hasLine, Line T1]
Generated description
Line T1 is a principal route of the Rouen tramway system in France, providing light rail transit service through key areas of the city and its suburbs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line T1
Target entity description: Line T1 is a principal route of the Rouen tramway system in France, providing light rail transit service through key areas of the city and its suburbs.
  • A. Line L
    Line L is a cable car line of the Medellín Metro system that serves hillside neighborhoods by connecting them to the main urban transit network.
  • B. Line 1
    Line 1 is the first operational corridor of the Mumbai Monorail system, serving as a key elevated transit route in Mumbai, India.
  • C. Line 1
    Line 1 is a primary Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
  • D. Line 1
    Line 1 is a major Milan Metro line that serves key areas of the city, including Milano Cadorna station.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d72e9d0f688190a9be024929d2f960 completed April 9, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69de2338b2cc8190ad40ff9a421a4152 completed April 14, 2026, 11:21 a.m.
NEDg Description generation batch_69de271ee56c81908d2f690f31c2d2db completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2dff4a048190823c8b5f1f7ea548 completed April 14, 2026, 12:07 p.m.
Created at: April 8, 2026, 9:15 p.m.