Triple

T105488
Position Surface form Disambiguated ID Type / Status
Subject Asia E2127 entity
Predicate containsMajorCity P316 FINISHED
Object Mumbai E9753 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: Mumbai | Statement: [Asia, containsMajorCity, Mumbai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mumbai
Context triple: [Asia, containsMajorCity, Mumbai]
  • A. Mumbai chosen
    Mumbai is a densely populated coastal metropolis in western India that serves as the country’s financial hub and the center of its film industry, Bollywood.
  • B. Pune
    Pune is a major cultural, educational, and IT hub in the western Indian state of Maharashtra, known for its universities, historical significance, and rapidly growing urban economy.
  • C. Ahmedabad
    Ahmedabad is a major city in the western Indian state of Gujarat, known for its rich history, textile industry, and role as an important economic and cultural center.
  • D. Calcutta
    Calcutta, now known as Kolkata, is a major cultural and commercial metropolis in eastern India that served as the capital of British India until the early 20th century.
  • E. Bengaluru
    Bengaluru is a major Indian metropolis known as the country’s leading technology and innovation hub, often called the “Silicon Valley of India.”
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a256c96e5481908c67f69e99978292 completed Feb. 28, 2026, 2:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2b85cc6b881909e2c13e70b24d934 completed Feb. 28, 2026, 9:41 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.