Triple

T19521021
Position Surface form Disambiguated ID Type / Status
Subject Charlotte's Web (2006 film) E488400 entity
Predicate editedBy P1954 FINISHED
Object Susan Littenberg 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: Susan Littenberg | Statement: [Charlotte's Web (2006 film), editedBy, Susan Littenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Littenberg
Context triple: [Charlotte's Web (2006 film), editedBy, Susan Littenberg]
  • A. Susan Littenberg chosen
    Susan Littenberg is a film editor known for her work on feature films such as the teen comedy "Easy A."
  • B. Judy Levitt
    Judy Levitt is an American actress best known for her long marriage to Star Trek actor Walter Koenig and for appearing in several of his film and television projects.
  • C. Arlene Litman
    Arlene Litman was the mother of American actress Lisa Bonet.
  • D. Susan Hendler
    Susan Hendler is a fictional character played by actress Caroline Goodall, likely appearing in a film or television production.
  • E. Linda Gottlieb
    Linda Gottlieb is an American film and television producer best known for producing the iconic 1987 romantic drama film "Dirty Dancing."
  • 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635a0b37c8190b70b7427c2e85f59 completed April 20, 2026, 2:18 p.m.
Created at: April 10, 2026, 1:40 p.m.