Triple

T13933962
Position Surface form Disambiguated ID Type / Status
Subject A Tree Grows in Brooklyn E335062 entity
Predicate author P4 FINISHED
Object Betty Smith E335062 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: Betty Smith | Statement: [A Tree Grows in Brooklyn, author, Betty Smith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Betty Smith
Context triple: [A Tree Grows in Brooklyn, author, Betty Smith]
  • A. Betty Smith
    Betty Smith is a fictional character from the animated television series "American Dad!", known as a member of Stan Smith's extended family.
  • B. Betty Smith chosen
    Betty Smith was an American author best known for her classic coming-of-age novel "A Tree Grows in Brooklyn."
  • C. Wendelin Van Draanen
    Wendelin Van Draanen is an American author best known for her young adult and children’s novels, including the popular book "Flipped."
  • D. Lois Duncan
    Lois Duncan was an American author best known for her suspenseful young adult novels that often blend mystery, psychological tension, and elements of the supernatural.
  • E. Judy Blume
    Judy Blume is a celebrated American author best known for her candid, influential novels for children and young adults that address adolescence, identity, and coming-of-age.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2cf28df081908d897d7b9ec7939d completed April 14, 2026, 12:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce865ab4819088221189344b3801 completed May 3, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:17 p.m.