Triple

T4028680
Position Surface form Disambiguated ID Type / Status
Subject The Now Show E83653 entity
Predicate hasCastMember P2308 FINISHED
Object Nish Kumar
Nish Kumar is a British stand-up comedian, actor, and radio presenter known for his sharp political satire and appearances on various UK comedy shows.
E409445 NE FINISHED

How this triple was built (4 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: Nish Kumar | Statement: [The Now Show, hasCastMember, Nish Kumar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nish Kumar
Context triple: [The Now Show, hasCastMember, Nish Kumar]
  • A. Nirvikar Singh
    Nirvikar Singh is an economist and academic known for his contributions to economic theory and policy, associated with leading institutions such as the Delhi School of Economics.
  • B. Vijay Kumar
    Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
  • C. Anshu Jain
    Anshu Jain was a prominent investment banker best known as the former co-CEO of Deutsche Bank and later a senior executive at Cantor Fitzgerald.
  • D. Rahul Banga
    Rahul Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
  • E. Yogesh Singh
    Yogesh Singh is an Indian academic and administrator who serves as the Vice-Chancellor of the University of Delhi.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nish Kumar
Triple: [The Now Show, hasCastMember, Nish Kumar]
Generated description
Nish Kumar is a British stand-up comedian, actor, and radio presenter known for his sharp political satire and appearances on various UK comedy shows.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nish Kumar
Target entity description: Nish Kumar is a British stand-up comedian, actor, and radio presenter known for his sharp political satire and appearances on various UK comedy shows.
  • A. Nirvikar Singh
    Nirvikar Singh is an economist and academic known for his contributions to economic theory and policy, associated with leading institutions such as the Delhi School of Economics.
  • B. Vijay Kumar
    Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
  • C. Anshu Jain
    Anshu Jain was a prominent investment banker best known as the former co-CEO of Deutsche Bank and later a senior executive at Cantor Fitzgerald.
  • D. Rahul Banga
    Rahul Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
  • E. Yogesh Singh
    Yogesh Singh is an Indian academic and administrator who serves as the Vice-Chancellor of the University of Delhi.
  • F. None of above. chosen

Provenance (5 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaf066b08190afbb4a18ddc8d67e completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556358f148190be7008092d0023af completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b55a5b292481908723530461bad562 completed March 14, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_69b55ae09ac48190a014aaf5b309e029 completed March 14, 2026, 12:56 p.m.
Created at: March 9, 2026, 3:36 p.m.