Triple

T8842101
Position Surface form Disambiguated ID Type / Status
Subject All I Ask E210411 entity
Predicate writer P1360 FINISHED
Object Christopher Brody Brown E369298 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: Christopher Brody Brown | Statement: [All I Ask, writer, Christopher Brody Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christopher Brody Brown
Context triple: [All I Ask, writer, Christopher Brody Brown]
  • A. Christopher Brody Brown chosen
    Christopher Brody Brown is an American songwriter and producer best known for his work with Bruno Mars on hit songs such as "Young, Wild & Free."
  • B. Jeremy Jordan
    Jeremy Jordan is an American actor and singer best known for his work on Broadway and in television musicals such as the series "Smash."
  • C. Jonah Platt
    Jonah Platt is an American actor and singer known for his work in musical theatre, television, and as part of the entertainment-industry Platt family.
  • D. Bradford Young
    Bradford Young is an acclaimed American cinematographer known for his evocative, naturalistic lighting and work on films such as Selma, Arrival, and Solo: A Star Wars Story.
  • E. Logan Marshall-Green
    Logan Marshall-Green is an American actor and director known for his roles in films like "Prometheus" and "Upgrade" as well as various television series.
  • 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60876c6c8190b1b490e447e1cf4b completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89a41a2c8190b69e5a1b157f9325 completed April 3, 2026, 9:34 a.m.
Created at: March 30, 2026, 6:48 p.m.