Triple

T7796282
Position Surface form Disambiguated ID Type / Status
Subject Metrocable Medellín E180305 entity
Predicate hasLine P35 FINISHED
Object Line P E688271 NE FINISHED

How this triple was built (2 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 P | Statement: [Metrocable Medellín, hasLine, Line P]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line P
Context triple: [Metrocable Medellín, hasLine, Line P]
  • A. Line P chosen
    Line P is a cable car line of the Medellín Metro system that serves hillside neighborhoods by connecting them to the city’s main mass transit network.
  • B. line P
    Line P is a Transilien suburban rail line serving the eastern suburbs of the Paris metropolitan area.
  • C. 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.
  • D. Line A
    Line A is one of the main lines of the Prague Metro, running east–west through the city and serving several central and residential districts.
  • E. Line A
    Line A is the historic first subway line of the Buenos Aires Underground, known for its early 20th-century wooden cars and route through central neighborhoods.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae94c41408190b73e37c0ff2c6628 completed March 30, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a18014c8190be64130bfb856e10 completed March 31, 2026, 5:22 a.m.
Created at: March 30, 2026, 4:32 p.m.