Triple

T30999692
Position Surface form Disambiguated ID Type / Status
Subject Larry Wilmore E789900 entity
Predicate correspondentOn P156089 FINISHED
Object The Daily Show 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: The Daily Show | Statement: [Larry Wilmore, correspondentOn, The Daily Show]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: correspondentOn
Context triple: [Larry Wilmore, correspondentOn, The Daily Show]
  • A. correspondentFor chosen
    Indicates that one entity serves as a correspondent or reporter on behalf of another entity, such as a media outlet, organization, or publication.
  • B. notableCorrespondent
    Indicates that one entity is a significant or distinguished correspondent of another, typically through notable or historically important exchanges of communication.
  • C. correspondedWith
    Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
  • D. correspondsWith
    Indicates that two entities are in mutual alignment or agreement, such that one matches, parallels, or is equivalent to the other in a specified respect.
  • E. correspondenceRelationshipWith
    Indicates a relationship in which two entities are connected through the exchange or maintenance of correspondence (such as letters, messages, or other communications).
  • F. None of above.

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_69f224c65a348190baaed1c01a29900c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f71422adac8190a5ceb32dcf820833 completed May 3, 2026, 9:23 a.m.
PD Predicate disambiguation batch_69f712764d2c819081b64b27e5de4a13 completed May 3, 2026, 9:16 a.m.
Created at: April 29, 2026, 8:56 p.m.