Triple

T6814220
Position Surface form Disambiguated ID Type / Status
Subject Tommy Boy E156711 entity
Predicate editedBy P1954 FINISHED
Object Don Zimmerman E109534 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: Don Zimmerman | Statement: [Tommy Boy, editedBy, Don Zimmerman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Zimmerman
Context triple: [Tommy Boy, editedBy, Don Zimmerman]
  • A. Don Zimmerman chosen
    Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
  • B. Dean Zimmerman
    Dean Zimmerman is an American film editor known for his work on major Hollywood action and science-fiction films.
  • C. Paul Zimmerer
    Paul Zimmerer was an American entrepreneur best known as the founder of Lindsay Corporation, a major manufacturer of agricultural irrigation and infrastructure equipment.
  • D. Daniel M. Ziegler
    Daniel M. Ziegler is a researcher known for co-authoring influential work in artificial intelligence and machine learning, including large language model research.
  • E. Donald Tokowitz
    Donald Tokowitz is better known as Donald Sterling, the former owner of the NBA's Los Angeles Clippers who became widely known for a major racism scandal that led to his lifetime ban from the league.
  • 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d32b012481909b73784899ec2a0d completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7425a26d88190ab1e3de2e5596108 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:17 p.m.