Triple

T13148317
Position Surface form Disambiguated ID Type / Status
Subject Charlie's Angels (2019 film) E312396 entity
Predicate editedBy P1954 FINISHED
Object Alan Baumgarten E250522 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: Alan Baumgarten | Statement: [Charlie's Angels (2019 film), editedBy, Alan Baumgarten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Baumgarten
Context triple: [Charlie's Angels (2019 film), editedBy, Alan Baumgarten]
  • A. Alan Baumgarten chosen
    Alan Baumgarten is an American film editor known for his work on a variety of feature films and television projects.
  • B. Eric Tannenbaum
    Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
  • C. Daniel Blumberg
    Daniel Blumberg is a British musician and composer known for his experimental work in indie rock and film scores.
  • D. Michael Greenberg
    Michael Greenberg is a prominent American neuroscientist renowned for his pioneering work on activity-dependent gene expression in the brain.
  • E. Michael Greenberg
    Michael Greenberg is an American businessman best known as the co-founder and longtime executive leader of the global footwear company Skechers.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bd0f5b08190ab700c5de1c8e138 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd19226eb881908f76134a04e72548 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 9:11 p.m.