Triple

T10364254
Position Surface form Disambiguated ID Type / Status
Subject Nordisk Film E244212 entity
Predicate foundedBy P104 FINISHED
Object Ole Olsen
Ole Olsen was a pioneering Danish film producer and entrepreneur who played a key role in the early development of the European film industry.
 E858107 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: Ole Olsen | Statement: [Nordisk Film, foundedBy, Ole Olsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ole Olsen
Context triple: [Nordisk Film, foundedBy, Ole Olsen]
  • A. Johan Jensen
    Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
  • B. Helge Petersen
    Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
  • C. Gunnar Hansen
    Gunnar Hansen was an Icelandic-American actor best known for originating the role of Leatherface in the 1974 horror classic "The Texas Chain Saw Massacre."
  • D. Thue Christiansen
    Thue Christiansen was a Greenlandic teacher, artist, and politician best known for creating Greenland’s national flag.
  • E. Ole Christensen
    Ole Christensen is a Danish mathematician known for his contributions to functional analysis and frame theory.
  • 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: Ole Olsen
Triple: [Nordisk Film, foundedBy, Ole Olsen]
Generated description
Ole Olsen was a pioneering Danish film producer and entrepreneur who played a key role in the early development of the European film industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ole Olsen
Target entity description: Ole Olsen was a pioneering Danish film producer and entrepreneur who played a key role in the early development of the European film industry.
  • A. Johan Jensen
    Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
  • B. Helge Petersen
    Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
  • C. Gunnar Hansen
    Gunnar Hansen was an Icelandic-American actor best known for originating the role of Leatherface in the 1974 horror classic "The Texas Chain Saw Massacre."
  • D. Thue Christiansen
    Thue Christiansen was a Greenlandic teacher, artist, and politician best known for creating Greenland’s national flag.
  • E. Ole Christensen
    Ole Christensen is a Danish mathematician known for his contributions to functional analysis and frame theory.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e964a53c8190b748e80850e96656 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750c2d2748190b871b928d5a094f8 completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618fac288190a5da7549e5ccbdf0 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77060331c8190a773a5f9ffadf1d6 completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, noon