Triple

T17876333
Position Surface form Disambiguated ID Type / Status
Subject Buster Baxter E446963 entity
Predicate creator P184 FINISHED
Object Marc Brown 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: Marc Brown | Statement: [Buster Baxter, creator, Marc Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marc Brown
Context triple: [Buster Baxter, creator, Marc Brown]
  • A. Marc Brown chosen
    Marc Brown is an American author and illustrator best known for creating the popular children's book and television series "Arthur."
  • B. Beatrice Bentley
    Beatrice Bentley was an actress known for her role in the early Technicolor silent film "The Toll of the Sea."
  • C. Joanna Cole
    Joanna Cole was an American children's author best known for writing the educational and humorous "The Magic School Bus" book series.
  • D. Pamela Gray
    Pamela Gray is an American screenwriter known for her work on character-driven drama films, including the military biographical film "Megan Leavey."
  • E. Angela C. Santomero
    Angela C. Santomero is a television producer and writer best known for creating influential educational children's shows such as Blue's Clues and Daniel Tiger's Neighborhood.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa614b48190bdc9e905e9e6d5e0 completed April 19, 2026, 9:04 a.m.
Created at: April 10, 2026, 10:18 a.m.