Triple

T22146852
Position Surface form Disambiguated ID Type / Status
Subject Shardul Thakur E547307 entity
Predicate stateTeam P74660 FINISHED
Object Mumbai NE NERFINISHED

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: [Shardul Thakur, stateTeam, Mumbai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mumbai
Context triple: [Shardul Thakur, stateTeam, 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. Bombay
    Bombay is a small rural settlement in the Auckland Region of New Zealand, located just south of the metropolitan area near the Bombay Hills.
  • C. Mambai
    Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f156988190bc9a24a37418e849 completed April 28, 2026, 9:43 p.m.
Created at: April 16, 2026, 8:33 p.m.