Triple

T4534568
Position Surface form Disambiguated ID Type / Status
Subject Shahdara–Tis Hazari E106375 entity
Predicate networkColor P34402 FINISHED
Object Red Line E180354 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: Red Line | Statement: [Shahdara–Tis Hazari, networkColor, Red Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red Line
Context triple: [Shahdara–Tis Hazari, networkColor, Red Line]
  • A. Red Line
    The Red Line is a primary route of the MetroLink light rail system serving key destinations in the St. Louis metropolitan area.
  • B. Red Line
    The Red Line is one of the primary heavy-rail rapid transit routes in Atlanta’s MARTA system, running north–south and serving key destinations across the metropolitan area.
  • C. Red Line
    Red Line was the original name of Los Angeles Metro’s B Line, a heavy-rail subway corridor serving key neighborhoods between Downtown Los Angeles and North Hollywood.
  • D. Red Line
    Red Line is one of the main rapid transit routes of the Dubai Metro, running along key areas of the city and serving many of its major commercial and residential districts.
  • E. Red Line chosen
    The Red Line is one of the major corridors of the Delhi Metro rapid transit system, serving numerous densely populated areas in and around Delhi.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57a2301c8190aa59280a16750156 completed March 20, 2026, 2:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be101759e08190b3190c6e8961b3f7 completed March 21, 2026, 3:27 a.m.
Created at: March 20, 2026, 1:04 p.m.