Triple

T13603344
Position Surface form Disambiguated ID Type / Status
Subject Skin (2018 film) E324996 entity
Predicate editedBy P1954 FINISHED
Object Yuval Orr
Yuval Orr is a film editor known for his work on the 2018 movie "Skin."
E1050062 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: Yuval Orr | Statement: [Skin (2018 film), editedBy, Yuval Orr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yuval Orr
Context triple: [Skin (2018 film), editedBy, Yuval Orr]
  • A. Oren Aviv
    Oren Aviv is an American film executive and producer known for his work on major Hollywood projects, including contributing to the story for the action-adventure film "National Treasure."
  • B. Oded Kotler
    Oded Kotler is an Israeli actor and theater director known for his prominent roles in film and stage as well as his influential work in Israeli performing arts.
  • C. Amir Yaron
    Amir Yaron is an Israeli-American economist who serves as the Governor of the Bank of Israel, overseeing the country’s monetary policy and financial stability.
  • D. Amnon Niv
    Amnon Niv is an Israeli architect best known for designing prominent high-rise buildings, including some of the country's most recognizable skyscrapers.
  • E. Yaron Orbach
    Yaron Orbach is a cinematographer known for his work on feature films and television, including the drama "Brain on Fire."
  • 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: Yuval Orr
Triple: [Skin (2018 film), editedBy, Yuval Orr]
Generated description
Yuval Orr is a film editor known for his work on the 2018 movie "Skin."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yuval Orr
Target entity description: Yuval Orr is a film editor known for his work on the 2018 movie "Skin."
  • A. Oren Aviv
    Oren Aviv is an American film executive and producer known for his work on major Hollywood projects, including contributing to the story for the action-adventure film "National Treasure."
  • B. Oded Kotler
    Oded Kotler is an Israeli actor and theater director known for his prominent roles in film and stage as well as his influential work in Israeli performing arts.
  • C. Amir Yaron
    Amir Yaron is an Israeli-American economist who serves as the Governor of the Bank of Israel, overseeing the country’s monetary policy and financial stability.
  • D. Amnon Niv
    Amnon Niv is an Israeli architect best known for designing prominent high-rise buildings, including some of the country's most recognizable skyscrapers.
  • E. Yaron Orbach
    Yaron Orbach is a cinematographer known for his work on feature films and television, including the drama "Brain on Fire."
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb07ca07481909c45da551ea61ab4 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f93ec588190993baec788d22670 completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f780bc40f481908191fec9a563e547 completed May 3, 2026, 5:07 p.m.
NED2 Entity disambiguation (via description) batch_69f7817b8c408190b7211ba8fd892f75 completed May 3, 2026, 5:10 p.m.
Created at: April 9, 2026, 9:49 p.m.