Triple

T14709397
Position Surface form Disambiguated ID Type / Status
Subject The Internship E345507 entity
Predicate editedBy P1954 FINISHED
Object Dean Zimmerman E527086 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: Dean Zimmerman | Statement: [The Internship, editedBy, Dean Zimmerman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dean Zimmerman
Context triple: [The Internship, editedBy, Dean Zimmerman]
  • A. Dean Zimmerman
    Dean Zimmerman is an American philosopher best known for his work in metaphysics, particularly on the nature of time, persistence, and the philosophy of religion.
  • B. Dean Zimmerman chosen
    Dean Zimmerman is an American film editor known for his work on major Hollywood action and science-fiction films.
  • C. Don Zimmerman
    Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
  • D. Gil Zimmerman
    Gil Zimmerman is a cinematographer best known for his work on the animated feature film "Monsters vs. Aliens."
  • E. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb9814e0c8190984ac30d276499cc completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff13322c548190bac21db2bfa56ee9 completed May 9, 2026, 10:57 a.m.
Created at: April 10, 2026, 1:28 a.m.