Triple

T12683538
Position Surface form Disambiguated ID Type / Status
Subject Hesher E303006 entity
Predicate productionCompany P490 FINISHED
Object Hesher Productions
Hesher Productions is the film production company behind the dark comedy-drama movie "Hesher."
 E997245 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: Hesher Productions | Statement: [Hesher, productionCompany, Hesher Productions]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hesher Productions
Context triple: [Hesher, productionCompany, Hesher Productions]
  • A. Ehsugadee Productions
    Ehsugadee Productions is a television production company best known for its work on the animated DC series "Harley Quinn."
  • B. Anhelo Productions
    Anhelo Productions is a film production company known for backing independent and character-driven movies such as "The Assassination of Richard Nixon."
  • C. Hear/Say Productions
    Hear/Say Productions is a film production company known for producing the acclaimed drama "Nomadland."
  • D. Morningside Productions
    Morningside Productions is a film production company best known for producing fantasy and adventure movies in the mid-20th century.
  • E. Jurow-Shepherd Productions
    Jurow-Shepherd Productions was a film production company best known for producing the classic 1961 romantic comedy "Breakfast at Tiffany's."
  • 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: Hesher Productions
Triple: [Hesher, productionCompany, Hesher Productions]
Generated description
Hesher Productions is the film production company behind the dark comedy-drama movie "Hesher."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hesher Productions
Target entity description: Hesher Productions is the film production company behind the dark comedy-drama movie "Hesher."
  • A. Ehsugadee Productions
    Ehsugadee Productions is a television production company best known for its work on the animated DC series "Harley Quinn."
  • B. Anhelo Productions
    Anhelo Productions is a film production company known for backing independent and character-driven movies such as "The Assassination of Richard Nixon."
  • C. Hear/Say Productions
    Hear/Say Productions is a film production company known for producing the acclaimed drama "Nomadland."
  • D. Morningside Productions
    Morningside Productions is a film production company best known for producing fantasy and adventure movies in the mid-20th century.
  • E. Jurow-Shepherd Productions
    Jurow-Shepherd Productions was a film production company best known for producing the classic 1961 romantic comedy "Breakfast at Tiffany's."
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961d68358819095bdaab8adf1dcf0 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a733a48190b55d296573c86eaf completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f67285019c8190be831d3f72cf121f completed May 2, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69f67323a724819092425cdb3a070b96 completed May 2, 2026, 9:56 p.m.
Created at: April 9, 2026, 5:21 p.m.