Triple

T10862803
Position Surface form Disambiguated ID Type / Status
Subject Nicola Mindel E256447 entity
Predicate spouse P13 FINISHED
Object Dan Mindel E51081 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: Dan Mindel | Statement: [Nicola Mindel, spouse, Dan Mindel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Mindel
Context triple: [Nicola Mindel, spouse, Dan Mindel]
  • A. Dan Mindel chosen
    Dan Mindel is a British cinematographer known for his work on major blockbuster films, including entries in the Star Trek and Star Wars franchises.
  • B. Daniel Mandell
    Daniel Mandell was an American film editor renowned for his work on numerous classic Hollywood films and for winning multiple Academy Awards for Best Film Editing.
  • C. Michael Markowitz
    Michael Markowitz is an American comedy writer best known for co-writing the hit film "Horrible Bosses."
  • D. Dan Shulman
    Dan Shulman is a Canadian sportscaster best known for his long-running play-by-play work on Major League Baseball and college basketball broadcasts for ESPN and other networks.
  • E. Jack Mandel
    Jack Mandel was a prominent philanthropist and businessman whose contributions to social work and education led to institutions such as the Jack, Joseph and Morton Mandel School of Applied Social Sciences being named in his honor.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7515238108190a72eb8cd147f223d completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69e482f327e48190ad087c232fd05609 completed April 19, 2026, 7:23 a.m.
Created at: April 8, 2026, 9:20 p.m.