Triple

T9429494
Position Surface form Disambiguated ID Type / Status
Subject Maulik Pancholy E227335 entity
Predicate name P16 FINISHED
Object Maulik Navin Pancholy E227335 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: Maulik Navin Pancholy | Statement: [Maulik Pancholy, name, Maulik Navin Pancholy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maulik Navin Pancholy
Context triple: [Maulik Pancholy, name, Maulik Navin Pancholy]
  • A. Maulik Pancholy chosen
    Maulik Pancholy is an American actor and author best known for his comedic television roles, including his portrayal of Jonathan on the sitcom "30 Rock."
  • B. Utkarsh Ambudkar
    Utkarsh Ambudkar is an American actor, rapper, and singer known for his work in film, television, and theater, including roles in projects like "Pitch Perfect," "Brittany Runs a Marathon," and the TV series "Ghosts."
  • C. Nick Mehta
    Nick Mehta is a technology executive best known as the CEO of Gainsight and a prominent advocate and thought leader in the field of customer success.
  • D. Rahul Bhatia
    Rahul Bhatia is an Indian businessman best known as the co-founder and key architect of IndiGo’s rise into India’s largest low-cost airline.
  • E. Pranav Shyam
    Pranav Shyam is a computer scientist and AI researcher known for co-authoring influential work in large-scale language models alongside Tom B. Brown and others.
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7c94719c81909d7743a57c45e07f completed April 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11038f7b88190bd6b895f5544c63e completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:49 p.m.