Triple

T4534573
Position Surface form Disambiguated ID Type / Status
Subject Shahdara–Tis Hazari E106375 entity
Predicate system P730 FINISHED
Object Delhi Metro Rail System E19472 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: Delhi Metro Rail System | Statement: [Shahdara–Tis Hazari, system, Delhi Metro Rail System]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Delhi Metro Rail System
Context triple: [Shahdara–Tis Hazari, system, Delhi Metro Rail System]
  • A. Delhi Metro chosen
    Delhi Metro is a rapid transit system serving Delhi and its surrounding metropolitan region, known for its extensive network, modern infrastructure, and role in easing urban congestion.
  • B. Noida Metro
    Noida Metro is a rapid transit system serving the city of Noida and its surrounding areas in India’s National Capital Region.
  • C. Mumbai Metro
    Mumbai Metro is a rapid transit system serving the Mumbai metropolitan region, designed to alleviate congestion and complement the city’s suburban railway network.
  • D. Kolkata Metro
    Kolkata Metro is India’s oldest rapid transit system, serving as a major urban rail network for the city of Kolkata and its surrounding areas.
  • E. Lucknow Metro
    Lucknow Metro is a rapid transit system serving the city of Lucknow in Uttar Pradesh, India, designed to provide fast, modern urban transportation.
  • 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_69be397d7358819086fa3851318973ea completed March 21, 2026, 6:23 a.m.
Created at: March 20, 2026, 1:04 p.m.