Triple

T21215242
Position Surface form Disambiguated ID Type / Status
Subject Archangel E522818 entity
Predicate author P4 FINISHED
Object Andrea Barrett 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: Andrea Barrett | Statement: [Archangel, author, Andrea Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrea Barrett
Context triple: [Archangel, author, Andrea Barrett]
  • A. Andrea Barrett chosen
    Andrea Barrett is an American novelist and short story writer best known for her historically rich, science-infused fiction, including the National Book Award–winning collection "Ship Fever."
  • B. Ann Beattie
    Ann Beattie is an American author renowned for her incisive short stories and novels depicting contemporary life and relationships, often associated with the minimalist literary movement.
  • C. Sue Miller
    Sue Miller is the wife of American musician Jeff Tweedy, frontman of the band Wilco.
  • D. Sue Miller
    Sue Miller is an American novelist known for her emotionally rich, psychologically nuanced explorations of family relationships and moral complexity.
  • E. Diane Johnson
    Diane Johnson is an American novelist and essayist best known for co-writing the screenplay for Stanley Kubrick’s film adaptation of Stephen King’s "The Shining."
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e734727a30819089c433e4fe6f438a completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:40 p.m.