Triple

T9060458
Position Surface form Disambiguated ID Type / Status
Subject A Fine Balance E217107 entity
Predicate settingCity P7747 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: [A Fine Balance, settingCity, Mumbai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mumbai
Context triple: [A Fine Balance, settingCity, 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. Mambai
    Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
  • C. Mumbai Metropolitan Region
    The Mumbai Metropolitan Region is a vast urban agglomeration in western India centered on Mumbai, encompassing the city and its surrounding suburbs and satellite towns.
  • D. 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.
  • E. 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.
  • 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_69ca83d4425481909a319dab847724ec completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc7eca6d8c8190b1a11a60d6649f78 completed April 1, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfebf4b9348190a7f01c64098c25f7 completed April 3, 2026, 4:33 p.m.
Created at: March 30, 2026, 7:10 p.m.