Triple

T7396378
Position Surface form Disambiguated ID Type / Status
Subject Deadpool 2 E170631 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: [Deadpool 2, producer, Lauren Shuler Donner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren Shuler Donner
Context triple: [Deadpool 2, 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. Heather Matarazzo
    Heather Matarazzo is an American actress best known for her character roles in films like "Welcome to the Dollhouse" and "The Princess Diaries."
  • D. Ari Wegner
    Ari Wegner is an acclaimed Australian cinematographer known for her visually striking work on films such as "The Power of the Dog."
  • E. Annie Mumolo
    Annie Mumolo is an American actress, comedian, and writer best known for co-writing the hit comedy film "Bridesmaids" with Kristen Wiig.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f248f79c819094b1d1e2c3d511d1 completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81101dd448190bcf221f7625c9d34 completed March 28, 2026, 5:33 p.m.
Created at: March 27, 2026, 3:09 p.m.