Triple

T10606086
Position Surface form Disambiguated ID Type / Status
Subject Mumbai Metro One Private Limited E275879 entity
Predicate lineTerminus P46766 FINISHED
Object Versova E275880 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: Versova | Statement: [Mumbai Metro One Private Limited, lineTerminus, Versova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Versova
Context triple: [Mumbai Metro One Private Limited, lineTerminus, Versova]
  • A. Versova chosen
    Versova is a coastal neighborhood in Mumbai, India, known for its beach, fishing village, and role as a key residential and commercial hub in the city.
  • B. Malaya Nevka
    Malaya Nevka is a distributary channel of the Neva River in Saint Petersburg, Russia, forming part of the city’s intricate river and canal network.
  • C. Охта
    Охта — это река на северо-западе России, протекающая через Санкт-Петербург и впадающая в Неву.
  • D. Vyatskoye
    Vyatskoye is a rural locality in Russia’s Khabarovsk Krai, historically noted as the birthplace of North Korean leader Kim Jong Il.
  • E. Kholmsk
    Kholmsk is a port town on the western coast of Sakhalin Island in Russia, serving as an important maritime transport hub in the Sea of Japan.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4a5df88190b993196ca7849a88 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b698f308190be8ee1e6bc8481d3 completed April 10, 2026, 9:28 p.m.
Created at: April 8, 2026, 7:32 p.m.