Triple

T22443538
Position Surface form Disambiguated ID Type / Status
Subject Suryakumar Yadav E554812 entity
Predicate hasPlayedDomesticCricketFor P67788 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: [Suryakumar Yadav, hasPlayedDomesticCricketFor, Mumbai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mumbai
Context triple: [Suryakumar Yadav, hasPlayedDomesticCricketFor, 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ae40f9081908674015beb33f74e completed April 29, 2026, 1:12 a.m.
Created at: April 16, 2026, 8:47 p.m.