Triple

T14225015
Position Surface form Disambiguated ID Type / Status
Subject Navi Mumbai E352594 entity
Predicate hasResidentialZone P9064 FINISHED
Object Belapur E948626 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: Belapur | Statement: [Navi Mumbai, hasResidentialZone, Belapur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belapur
Context triple: [Navi Mumbai, hasResidentialZone, Belapur]
  • A. Belapur chosen
    Belapur is a major suburban node in Navi Mumbai, India, known for its commercial centers, residential areas, and role as a key transport hub.
  • B. Ghatkopar
    Ghatkopar is a densely populated residential and commercial suburb in eastern Mumbai, known for its bustling markets, connectivity, and vibrant Gujarati community.
  • C. Bhandup
    Bhandup is a suburban residential and industrial locality in the northeastern part of Mumbai, India.
  • D. Chembur
    Chembur is a prominent suburban neighborhood in eastern Mumbai known for its residential areas, connectivity, and growing commercial and industrial presence.
  • E. Vikhroli
    Vikhroli is a suburban neighborhood in Mumbai known for its residential areas, industrial estates, and proximity to major transport links.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6228e53c8190abbe4e2d88a7362a completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda904f8ac8190a4206b6ab6ee812c completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:06 a.m.