Triple

T13143939
Position Surface form Disambiguated ID Type / Status
Subject Biotrén E312286 entity
Predicate hasLine P35 FINISHED
Object Line 2
Line 2 is one of the commuter rail lines of the Biotrén system serving the Greater Concepción area in Chile.
E1029243 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: [Biotrén, hasLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Biotrén, hasLine, Line 2]
  • A. 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.
  • 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 rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
  • D. Line 2
    Line 2 is the Yellow Line of the Delhi Metro, a major rapid transit corridor connecting key areas across Delhi and its neighboring regions.
  • E. Line 2
    Line 2 is a major rapid transit line of the Chongqing Metro system in Chongqing, China, known for being one of the city's primary monorail 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: [Biotrén, hasLine, Line 2]
Generated description
Line 2 is one of the commuter rail lines of the Biotrén system serving the Greater Concepción area in Chile.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 2
Target entity description: Line 2 is one of the commuter rail lines of the Biotrén system serving the Greater Concepción area in Chile.
  • 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 one of the principal lines of the Mexico City Metro system, running across key central and western areas of the city and serving as a major high-capacity transit corridor.
  • C. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • D. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • E. Line 2
    Line 2 is a major east–west rapid transit route of the Nanjing Metro system in Nanjing, China, connecting key urban districts and transportation hubs.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bce3678819082a7aa1d83f20592 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff09a964819097fbb37a7f11eac5 completed May 3, 2026, 7:53 a.m.
NEDg Description generation batch_69f701e348d881908db3622cc8e082c3 completed May 3, 2026, 8:05 a.m.
NED2 Entity disambiguation (via description) batch_69f7031a4490819081da260edd969ee8 completed May 3, 2026, 8:11 a.m.
Created at: April 9, 2026, 9:10 p.m.