Triple

T15063971
Position Surface form Disambiguated ID Type / Status
Subject The Babysitter E379707 entity
Predicate editedBy P1954 FINISHED
Object Peter Gvozdas
Peter Gvozdas is a film editor known for his work on the movie "The Babysitter."
E1141991 NE FINISHED

How this triple was built (4 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: Peter Gvozdas | Statement: [The Babysitter, editedBy, Peter Gvozdas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Gvozdas
Context triple: [The Babysitter, editedBy, Peter Gvozdas]
  • A. Joe Pisarcik
    Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
  • B. Philip LaZebnik
    Philip LaZebnik is an American screenwriter and playwright best known for his work on animated feature films such as Disney’s "Mulan" and "Pocahontas" and DreamWorks’ "The Prince of Egypt."
  • C. Denis Kosiak
    Denis Kosiak is a music producer best known for his work on the project American Teen.
  • D. Roman Podhora
    Roman Podhora is a Canadian actor known for his work in film and television, including roles in genre and action projects.
  • E. Vladimir Smicer
    Vladimir Šmicer is a retired Czech attacking midfielder best known for scoring in Liverpool’s dramatic comeback victory over AC Milan in the 2005 UEFA Champions League Final, known as the “Miracle of Istanbul.”
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Peter Gvozdas
Triple: [The Babysitter, editedBy, Peter Gvozdas]
Generated description
Peter Gvozdas is a film editor known for his work on the movie "The Babysitter."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peter Gvozdas
Target entity description: Peter Gvozdas is a film editor known for his work on the movie "The Babysitter."
  • A. Joe Pisarcik
    Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
  • B. Philip LaZebnik
    Philip LaZebnik is an American screenwriter and playwright best known for his work on animated feature films such as Disney’s "Mulan" and "Pocahontas" and DreamWorks’ "The Prince of Egypt."
  • C. Denis Kosiak
    Denis Kosiak is a music producer best known for his work on the project American Teen.
  • D. Roman Podhora
    Roman Podhora is a Canadian actor known for his work in film and television, including roles in genre and action projects.
  • E. Vladimir Smicer
    Vladimir Šmicer is a retired Czech attacking midfielder best known for scoring in Liverpool’s dramatic comeback victory over AC Milan in the 2005 UEFA Champions League Final, known as the “Miracle of Istanbul.”
  • F. None of above. chosen

Provenance (5 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedee803ac81908bb7d66e49c2eb72 completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fec878c52c8190bf010b1fd4d21f65 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fecc54e7a08190bcdc6a53508dd9e7 completed May 9, 2026, 5:55 a.m.
NED2 Entity disambiguation (via description) batch_69feccca7d908190b0be236cf18e7b4c completed May 9, 2026, 5:57 a.m.
Created at: April 10, 2026, 3:02 a.m.