Triple

T3376550
Position Surface form Disambiguated ID Type / Status
Subject Hyderabad Metro E71079 entity
Predicate hasLine P35 FINISHED
Object Red Line
Red Line is one of the main rapid transit corridors of the Hyderabad Metro system in Hyderabad, India.
E366308 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: Red Line | Statement: [Hyderabad Metro, hasLine, Red Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Line
Context triple: [Hyderabad Metro, hasLine, Red Line]
  • A. Red Line
    The Red Line is a major rapid transit route in Chicago that runs north–south through the city, serving as one of the busiest lines in its subway and elevated rail system.
  • B. Red Line
    Red Line is a major rapid transit route in the Washington Metro system, running through key areas of Washington, D.C., and its Maryland suburbs.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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: Red Line
Triple: [Hyderabad Metro, hasLine, Red Line]
Generated description
Red Line is one of the main rapid transit corridors of the Hyderabad Metro system in Hyderabad, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Red Line
Target entity description: Red Line is one of the main rapid transit corridors of the Hyderabad Metro system in Hyderabad, India.
  • A. Red Line
    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.
  • B. 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.
  • C. Red Line
    The Red Line is a major light rail route in the Dallas Area Rapid Transit (DART) system serving key corridors across the Dallas–Fort Worth metro area.
  • D. Red Line
    Red Line is a major rapid transit route in the Washington Metro system, running through key areas of Washington, D.C., and its Maryland suburbs.
  • E. 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.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2e776508190bc123fb17b36f062 completed March 8, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e503d94819082657f11d51aebca completed March 13, 2026, 3:02 a.m.
NEDg Description generation batch_69b38232467c81909eb831bb0747cb77 completed March 13, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_69b385f078d48190a72e61c59aa27e43 completed March 13, 2026, 3:35 a.m.
Created at: March 8, 2026, 3:13 p.m.