Triple

T12394965
Position Surface form Disambiguated ID Type / Status
Subject Gruta de Lourdes station E296092 entity
Predicate servedBy P82 FINISHED
Object Line 5
Line 5 is a route of the Santiago Metro system in Chile, connecting various neighborhoods across the city as part of its urban rapid transit network.
E61190 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 5 | Statement: [Gruta de Lourdes station, servedBy, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Gruta de Lourdes station, servedBy, Line 5]
  • A. Line 5
    Line 5 is a commuter rail line of the Tehran Metro system that connects central Tehran with its western suburbs and satellite cities.
  • B. Line 5
    Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
  • C. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • D. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • E. Line 5
    Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
  • 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 5
Triple: [Gruta de Lourdes station, servedBy, Line 5]
Generated description
Line 5 is a route of the Santiago Metro system in Chile, connecting various neighborhoods across the city as part of its urban rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is a route of the Santiago Metro system in Chile, connecting various neighborhoods across the city as part of its urban rapid transit network.
  • A. Line 5 chosen
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • B. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • C. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
  • D. Line 5
    Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
  • E. Line 5
    Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd33f048190b205fd21dc513f6a completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6347e27b4819085494babfe180488 completed May 2, 2026, 5:29 p.m.
NEDg Description generation batch_69f63674aa3c81908ba82a9d246b3b3a completed May 2, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_69f63a9b32fc8190ab98492ff91d2a66 completed May 2, 2026, 5:55 p.m.
Created at: April 8, 2026, 9:54 p.m.