Triple

T13294565
Position Surface form Disambiguated ID Type / Status
Subject Baquedano station E316647 entity
Predicate connectsWith P37 FINISHED
Object Line 5
Line 5 is one of the main lines of the Santiago Metro in Chile, running through key residential and commercial areas and intersecting with several other lines.
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: [Baquedano station, connectsWith, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Baquedano station, connectsWith, 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: [Baquedano station, connectsWith, Line 5]
Generated description
Line 5 is one of the main lines of the Santiago Metro in Chile, running through key residential and commercial areas and intersecting with several other lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is one of the main lines of the Santiago Metro in Chile, running through key residential and commercial areas and intersecting with several other lines.
  • 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 a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
  • C. 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.
  • 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 a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99079c8508190b6208db9affcbc0e completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716d8ee2081908428339216c43b47 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f717b7b6dc8190ab323c1926dd9adb completed May 3, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_69f7186b6218819096c67e9dd9af609f completed May 3, 2026, 9:42 a.m.
Created at: April 9, 2026, 9:28 p.m.