Triple

T10325640
Position Surface form Disambiguated ID Type / Status
Subject Tully E242753 entity
Predicate editedBy P1954 FINISHED
Object Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
E857067 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: Stefan Grube | Statement: [Tully, editedBy, Stefan Grube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stefan Grube
Context triple: [Tully, editedBy, Stefan Grube]
  • A. Stefan Grube
    Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
  • B. Andreas Huber
    Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
  • C. Markus Sattler
    Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
  • D. Johann Schwarzhuber
    Johann Schwarzhuber was an SS officer and concentration camp official in Nazi Germany who was prosecuted for war crimes after World War II.
  • E. Stefan Butz
    Stefan Butz is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Butz.
  • 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: Stefan Grube
Triple: [Tully, editedBy, Stefan Grube]
Generated description
Stefan Grube is an editor known for his work on the film "Tully."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stefan Grube
Target entity description: Stefan Grube is an editor known for his work on the film "Tully."
  • A. Stefan Grube
    Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
  • B. Andreas Huber
    Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
  • C. Markus Sattler
    Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
  • D. Johann Schwarzhuber
    Johann Schwarzhuber was an SS officer and concentration camp official in Nazi Germany who was prosecuted for war crimes after World War II.
  • E. Stefan Butz
    Stefan Butz is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Butz.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7cd76348190b93562112300acfc completed April 7, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7503f3df88190bc5acb5e5295f787 completed April 9, 2026, 7:07 a.m.
NEDg Description generation batch_69d7516a4d088190b3e3b86956b6b821 completed April 9, 2026, 7:12 a.m.
NED2 Entity disambiguation (via description) batch_69d75200eecc819094e261c9fa7c75f5 completed April 9, 2026, 7:15 a.m.
Created at: April 6, 2026, 11:51 a.m.