Triple

T37115238
Position Surface form Disambiguated ID Type / Status
Subject Chhatrapati Shivaji Maharaj Terminus E919098 entity
Predicate hasSuburbanConcourse P201967 FINISHED
Object yes LITERAL 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: yes | Statement: [Chhatrapati Shivaji Maharaj Terminus, hasSuburbanConcourse, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSuburbanConcourse
Context triple: [Chhatrapati Shivaji Maharaj Terminus, hasSuburbanConcourse, yes]
  • A. hasSuburbanSection
    Indicates that a larger route, line, or area includes a portion that passes through or serves a suburban region.
  • B. hasSuburbanTerminus
    Indicates that a transportation route or service ends at a terminus located in a suburban area.
  • C. hasSuburbanPlatforms
    Indicates that an entity (typically a railway station or transit hub) includes platforms specifically designated for suburban or commuter train services.
  • D. hasIndoorConcourse
    Indicates that one place is connected to another by an indoor concourse or passageway.
  • E. hasSuburbanService
    Indicates that an entity provides or is connected to a public transportation service specifically serving suburban areas, typically linking suburbs with urban centers.
  • F. None of above. chosen

Provenance (4 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_69f76e9c57148190ba789dd059645bb9 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 completed May 10, 2026, 7:54 a.m.
PD Predicate disambiguation batch_6a0038e525448190a4c815f51595e78d completed May 10, 2026, 7:51 a.m.
PDg Predicate description generation batch_6a0039c1eec48190963671a5b8c5f631 completed May 10, 2026, 7:54 a.m.
Created at: May 3, 2026, 4:15 p.m.