Triple

T8503058
Position Surface form Disambiguated ID Type / Status
Subject Penn & Teller: Fool Us E201268 entity
Predicate hasCastMember P2308 FINISHED
Object Jonathan Ross E181760 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: Jonathan Ross | Statement: [Penn & Teller: Fool Us, hasCastMember, Jonathan Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Ross
Context triple: [Penn & Teller: Fool Us, hasCastMember, Jonathan Ross]
  • A. Jonathan Ross chosen
    Jonathan Ross is a British television and radio presenter best known for hosting long-running chat shows such as "Friday Night with Jonathan Ross."
  • B. Jonathan Stephen Ross
    Jonathan Stephen Ross is a British television and radio presenter best known for hosting long-running chat shows such as "Friday Night with Jonathan Ross."
  • C. Scott Ross
    Scott Ross is a musician best known as a member of the early 1990s hip hop group Marky Mark and the Funky Bunch.
  • D. Daniel Ross
    Daniel Ross is an American voice actor best known for portraying iconic animated characters, including voicing Donald Duck in various Disney productions.
  • E. Daniel Ross
    Daniel Ross is the son of John Ross, likely known primarily in relation to his father.
  • 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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe59c413881909513d8a9d52333c0 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d257a748190b33873ee0d252d2e completed April 2, 2026, 1:20 p.m.
Created at: March 30, 2026, 6:14 p.m.