Triple

T10394599
Position Surface form Disambiguated ID Type / Status
Subject Catch a Fire (2006 film) E244979 entity
Predicate producer P490 FINISHED
Object Stacey Sher E130841 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: Stacey Sher | Statement: [Catch a Fire (2006 film), producer, Stacey Sher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stacey Sher
Context triple: [Catch a Fire (2006 film), producer, Stacey Sher]
  • A. Stacey Sher chosen
    Stacey Sher is an American film and television producer known for her work on acclaimed movies such as "Django Unchained," "Pulp Fiction," and "Erin Brockovich."
  • B. Stacy Haiduk
    Stacy Haiduk is an American actress known for her work in television, including prominent roles in series such as seaQuest DSV, Superboy, and various daytime soap operas.
  • C. Valerie Faris
    Valerie Faris is an American film and music video director best known for co-directing acclaimed features such as "Little Miss Sunshine" and other character-driven comedies and dramas.
  • D. Jodi Wexler
    Jodi Wexler is an actress best known for her role in the film "The Love Machine."
  • E. Lesli Linka Glatter
    Lesli Linka Glatter is an American television director and producer known for her work on acclaimed series such as Homeland, Mad Men, and The West Wing.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9ce6bb08190bfeaba98a126526d completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e7adc3881909731d5289f370b8b completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:06 p.m.