Triple

T2865244
Position Surface form Disambiguated ID Type / Status
Subject You've Got Mail E63422 entity
Predicate producer P490 FINISHED
Object Lauren Shuler Donner E166986 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: Lauren Shuler Donner | Statement: [You've Got Mail, producer, Lauren Shuler Donner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren Shuler Donner
Context triple: [You've Got Mail, producer, Lauren Shuler Donner]
  • A. Lauren Shuler Donner chosen
    Lauren Shuler Donner is an American film producer best known for her work on major studio films including the X-Men franchise and other popular Hollywood features.
  • B. Natalie Desselle
    Natalie Desselle was an American actress best known for her comedic roles in film and television, including her memorable performance in the 1997 adaptation of "Cinderella."
  • C. Ari Wegner
    Ari Wegner is an acclaimed Australian cinematographer known for her visually striking work on films such as "The Power of the Dog."
  • D. Annie Mumolo
    Annie Mumolo is an American actress, comedian, and writer best known for co-writing the hit comedy film "Bridesmaids" with Kristen Wiig.
  • E. Adeena Sussman
    Adeena Sussman is an American-Israeli cookbook author and food writer known for her vibrant, flavor-forward recipes and collaborations with prominent culinary figures.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfb9e64c819087b1a47caeb174d5 completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055e6a7988190b37381667ec26fef completed March 10, 2026, 5:33 p.m.
Created at: March 6, 2026, 10:02 p.m.