Triple

T13828455
Position Surface form Disambiguated ID Type / Status
Subject Vikhroli E332315 entity
Predicate adjacentTo P224 FINISHED
Object Bhandup E280946 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: Bhandup | Statement: [Vikhroli, adjacentTo, Bhandup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhandup
Context triple: [Vikhroli, adjacentTo, Bhandup]
  • A. Bhandup chosen
    Bhandup is a suburban residential and industrial locality in the northeastern part of Mumbai, India.
  • 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. Belapur
    Belapur is a major suburban node in Navi Mumbai, India, known for its commercial centers, residential areas, and role as a key transport hub.
  • D. Vikhroli
    Vikhroli is a suburban neighborhood in Mumbai known for its residential areas, industrial estates, and proximity to major transport links.
  • E. Andheri
    Andheri is a major residential, commercial, and transport hub in Mumbai, India, known for its busy railway station, metro connectivity, and proximity to the city’s airports and film industry areas.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02970df88190a1bf35dffd131d9d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a2df73c8190aeb6f472ac7ebeed completed May 8, 2026, 5:52 a.m.
Created at: April 9, 2026, 10:13 p.m.