Triple

T3993433
Position Surface form Disambiguated ID Type / Status
Subject Ross E87043 entity
Predicate hasNotableBearer P458 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: [Ross, hasNotableBearer, Jonathan Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Ross
Context triple: [Ross, hasNotableBearer, 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. Daniel Ross
    Daniel Ross is an American voice actor best known for portraying iconic animated characters, including voicing Donald Duck in various Disney productions.
  • C. Christian Ross
    Christian Ross was the wife of Scottish poet Allan Ramsay, known primarily through her connection to the influential 18th-century literary figure.
  • D. Steve Ross
    Steve Ross was an American businessman best known for building Warner Communications into a media powerhouse and serving as a key architect of what became Time Warner.
  • E. Bill Ross IV
    Bill Ross IV is an American cinematographer and filmmaker known for his work on documentaries, including the acclaimed film "I Am Not Your Negro."
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa1d9d8c8190982d092a73d38564 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5403970e08190bb491048b1bd7b16 completed March 14, 2026, 11:02 a.m.
Created at: March 9, 2026, 3:33 p.m.