Triple

T11500112
Position Surface form Disambiguated ID Type / Status
Subject Mumbai Metropolitan Region Development Authority E272640 entity
Predicate serviceArea P82 FINISHED
Object Thane E168787 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: Thane | Statement: [Mumbai Metropolitan Region Development Authority, serviceArea, Thane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thane
Context triple: [Mumbai Metropolitan Region Development Authority, serviceArea, Thane]
  • A. Thane chosen
    Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
  • B. Panvel
    Panvel is a major railway and commercial hub in Navi Mumbai, Maharashtra, serving as an important junction and gateway between Mumbai and the wider Konkan region.
  • C. Navi Mumbai
    Navi Mumbai is a planned satellite city across the harbor from Mumbai, developed to decongest the main metropolis and featuring organized residential, commercial, and industrial zones.
  • D. Kurla
    Kurla is a densely populated suburban neighborhood in Mumbai, India, known as a major residential, commercial, and transport hub of the city.
  • E. Mumbra
    Mumbra is a densely populated suburban area in the Thane district of Maharashtra, India, known for its largely Muslim population and rapid urban growth.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85de3e9c881909d6c55334f7a832d completed April 10, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f69b76e0cc8190aa7303347e0183d4 completed May 3, 2026, 12:48 a.m.
Created at: April 8, 2026, 9:36 p.m.