Triple

T23063218
Position Surface form Disambiguated ID Type / Status
Subject Norah Silverberg E574960 entity
Predicate createdBy P806 FINISHED
Object David Levithan 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: David Levithan | Statement: [Norah Silverberg, createdBy, David Levithan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Levithan
Context triple: [Norah Silverberg, createdBy, David Levithan]
  • A. David Levithan chosen
    David Levithan is an American author and editor known for his young adult novels that often explore LGBTQ+ themes and contemporary teen relationships.
  • B. John Green
    John Green is an American author and YouTube creator best known for his bestselling young adult novels such as "The Fault in Our Stars" and "Looking for Alaska."
  • C. John Green
    John Green was an American statesman who represented South Carolina as a delegate to the Continental Congress during the Revolutionary era.
  • D. John Green
    John Green was a 19th-century English architect and engineer known for designing notable structures in northern England, including prominent monuments and bridges.
  • E. Tim Federle
    Tim Federle is an American author, screenwriter, and director best known for creating the Disney+ series "High School Musical: The Musical: The Series" and co-writing the animated film "Ferdinand."
  • 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_69e245bd6e4c8190bb8942245b68cad5 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f189a1f49c81909db7e0473ec2bb1b completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.