Triple

T5074183
Position Surface form Disambiguated ID Type / Status
Subject Lille Metro E114351 entity
Predicate line P1293 FINISHED
Object Line 2
Line 2 is one of the two automated light metro lines of the Lille Metro system in northern France, serving numerous stations across the metropolitan area.
E496538 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: [Lille Metro, line, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Lille Metro, line, 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 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 planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
  • D. 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.
  • E. 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.
  • 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: [Lille Metro, line, Line 2]
Generated description
Line 2 is one of the two automated light metro lines of the Lille Metro system in northern France, serving numerous stations across the metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 2
Target entity description: Line 2 is one of the two automated light metro lines of the Lille Metro system in northern France, serving numerous stations across the metropolitan area.
  • A. Line 2
    Line 2 is a circular line of the Brussels Metro system that serves central and surrounding districts of the Belgian capital.
  • B. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • C. Line 2
    Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
  • 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 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

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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d0be1c819081b26235fe602a30 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec35e7b848190bbb4cea9d09531e0 completed March 21, 2026, 4:12 p.m.
NEDg Description generation batch_69bec505a5dc81908f79c1ade107c4ce completed March 21, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69bec654fc4881909bf5458cdafc7ffd completed March 21, 2026, 4:24 p.m.
Created at: March 20, 2026, 1:39 p.m.