Triple

T4956061
Position Surface form Disambiguated ID Type / Status
Subject Mathura Road E111282 entity
Predicate hasJunctionWith P1018 FINISHED
Object Lodhi Road E394083 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: Lodhi Road | Statement: [Mathura Road, hasJunctionWith, Lodhi Road]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lodhi Road
Context triple: [Mathura Road, hasJunctionWith, Lodhi Road]
  • A. Lodhi Road chosen
    Lodhi Road is a major thoroughfare in New Delhi, India, known for its government offices, cultural institutions, and proximity to historic sites and green spaces.
  • B. Akbar Road
    Akbar Road is a prominent, historically significant thoroughfare in New Delhi that houses several important political offices and residences.
  • C. Mathura Road
    Mathura Road is a major arterial roadway in Delhi that forms part of National Highway 44 and connects central Delhi with its southern and southeastern suburbs.
  • D. Jawaharlal Nehru Road
    Jawaharlal Nehru Road is a major thoroughfare in central Kolkata, India, known for its historic landmarks, commercial activity, and cultural institutions.
  • E. Sohna Road
    Sohna Road is a major commercial and residential corridor in Gurugram, India, known for its office complexes, malls, and rapidly developing urban infrastructure.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71babb44819085b4cd4864433e79 completed March 20, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89f639c081908658c1a228081dd9 completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:32 p.m.