Triple

T14347238
Position Surface form Disambiguated ID Type / Status
Subject Blue Line (Namma Metro) E355757 entity
Predicate shortName P43 FINISHED
Object Blue Line E355757 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: Blue Line | Statement: [Blue Line (Namma Metro), shortName, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Line
Context triple: [Blue Line (Namma Metro), shortName, Blue Line]
  • A. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • B. Blue Line
    The Blue Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key neighborhoods and suburbs in the Dallas–Fort Worth metroplex.
  • C. Blue Line
    The Blue Line is one of the primary routes of the MetroLink light rail system serving the St. Louis metropolitan area.
  • D. Blue Line chosen
    The Blue Line is a planned rapid transit corridor of Bengaluru’s Namma Metro network intended to expand connectivity across additional parts of the city.
  • E. Blue Line
    The Blue Line is one of the aerial cable car routes in La Paz–El Alto’s Mi Teleférico urban transit system, providing high-altitude public transportation across the Bolivian cities.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8b81bc8190ace2a575faf55cc0 completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c2e7ee081909a70c9d9b32b6ce5 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:14 a.m.