Triple

T1111596
Position Surface form Disambiguated ID Type / Status
Subject Mumbai English E11007 entity
Predicate spokenIn P2266 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: [Mumbai English, spokenIn, Mumbai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mumbai
Context triple: [Mumbai English, spokenIn, 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. Delhi
    Delhi is a major metropolitan region and the capital territory of India, known for its political significance, rich history, and diverse culture.
  • D. 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.
  • E. 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.
  • 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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bb7742788190b320aec99e76ca41 completed March 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad58a2448c81909cb30e1a4400e1f3 completed March 8, 2026, 11:08 a.m.
Created at: March 1, 2026, 7:43 p.m.