Triple

T8784377
Position Surface form Disambiguated ID Type / Status
Subject Human Flow E209007 entity
Predicate producer P490 FINISHED
Object Heino Deckert
Heino Deckert is a German film producer and documentary filmmaker known for his work on internationally acclaimed non-fiction films.
E757379 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: Heino Deckert | Statement: [Human Flow, producer, Heino Deckert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heino Deckert
Context triple: [Human Flow, producer, Heino Deckert]
  • A. Rob Simonsen
    Rob Simonsen is an American film composer known for his emotive, atmospheric scores for contemporary dramas and comedies.
  • B. Jens Beckert
    Jens Beckert is a German sociologist renowned for his work on economic sociology, particularly the role of expectations and uncertainty in markets.
  • C. Markus Rygaard
    Markus Rygaard is a Danish actor best known for his leading role as a troubled schoolboy in the Oscar-winning film "In a Better World."
  • D. Jesper Rasmussen
    Jesper Rasmussen is a Danish professional footballer known for playing as a forward in Denmark’s top leagues.
  • E. Joachim Lemelsen
    Joachim Lemelsen was a German Wehrmacht general during World War II who held several high-ranking field commands on the Eastern and Italian fronts.
  • 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: Heino Deckert
Triple: [Human Flow, producer, Heino Deckert]
Generated description
Heino Deckert is a German film producer and documentary filmmaker known for his work on internationally acclaimed non-fiction films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Heino Deckert
Target entity description: Heino Deckert is a German film producer and documentary filmmaker known for his work on internationally acclaimed non-fiction films.
  • A. Rob Simonsen
    Rob Simonsen is an American film composer known for his emotive, atmospheric scores for contemporary dramas and comedies.
  • B. Jens Beckert
    Jens Beckert is a German sociologist renowned for his work on economic sociology, particularly the role of expectations and uncertainty in markets.
  • C. Markus Rygaard
    Markus Rygaard is a Danish actor best known for his leading role as a troubled schoolboy in the Oscar-winning film "In a Better World."
  • D. Jesper Rasmussen
    Jesper Rasmussen is a Danish professional footballer known for playing as a forward in Denmark’s top leagues.
  • E. Joachim Lemelsen
    Joachim Lemelsen was a German Wehrmacht general during World War II who held several high-ranking field commands on the Eastern and Italian fronts.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f7441e8819081ea0ae7bc2afde7 completed March 31, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51f41eb081909124a5e74333a31d completed April 3, 2026, 5:36 a.m.
NEDg Description generation batch_69cf55ec47f88190878724c4245410de completed April 3, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_69cf5679f85c8190aebb19ad364fe202 completed April 3, 2026, 5:56 a.m.
Created at: March 30, 2026, 6:42 p.m.