Triple

T9908797
Position Surface form Disambiguated ID Type / Status
Subject Blue Line (Delhi Metro) E185085 entity
Predicate lineNumber P1864 FINISHED
Object Line 3
Line 3 is a major corridor of the Delhi Metro’s Blue Line, serving as one of the primary rapid transit routes across the city.
E829355 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 3 | Statement: [Blue Line (Delhi Metro), lineNumber, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 3
Context triple: [Blue Line (Delhi Metro), lineNumber, Line 3]
  • A. Line 3
    Line 3 is a rapid transit line of the Toronto subway system, commonly known as the Scarborough RT, that served the Scarborough district.
  • B. Line 3
    Line 3 is a future rapid transit route of the Seville Metro intended to extend and improve the city’s urban rail network.
  • C. Line 3
    Line 3 is a major line of the Sofia Metro rapid transit system in Sofia, Bulgaria, serving key residential and commercial areas of the city.
  • D. Line 3
    Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
  • E. Line 3
    Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
  • 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 3
Triple: [Blue Line (Delhi Metro), lineNumber, Line 3]
Generated description
Line 3 is a major corridor of the Delhi Metro’s Blue Line, serving as one of the primary rapid transit routes across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 3
Target entity description: Line 3 is a major corridor of the Delhi Metro’s Blue Line, serving as one of the primary rapid transit routes across the city.
  • A. Line 3
    Line 3 is a major rapid transit route of the STC Metro system, serving key districts along its corridor.
  • B. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • C. Line 3
    Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
  • D. Line 3
    Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
  • E. Line 3
    Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50feb008190aa9c084f590c0ebd completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20daabd5881908b02da50a640766a completed April 5, 2026, 7:22 a.m.
NEDg Description generation batch_69d20ef343a4819093b915a66c63fbaa completed April 5, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_69d212d0ed108190bbde23439734618a completed April 5, 2026, 7:44 a.m.
Created at: March 30, 2026, 8:41 p.m.