Triple

T10393913
Position Surface form Disambiguated ID Type / Status
Subject Göran E244957 entity
Predicate hasNotableBearer P458 FINISHED
Object Göran Gillinger
Göran Gillinger is a Swedish actor known for his work in film, television, and theater.
E879318 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: Göran Gillinger | Statement: [Göran, hasNotableBearer, Göran Gillinger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göran Gillinger
Context triple: [Göran, hasNotableBearer, Göran Gillinger]
  • A. Göran Rosenberg
    Göran Rosenberg is a Swedish journalist, author, and public intellectual known for his works on politics, history, and the Jewish experience in Sweden.
  • B. Arvid Genetz
    Arvid Genetz was a Finnish linguist, poet, and politician known for his contributions to Finno-Ugric language studies and his role in the Finnish national movement.
  • C. Ferdinand Boberg
    Ferdinand Boberg was a prominent Swedish architect of the late 19th and early 20th centuries, known for his influential contributions to national romantic and Art Nouveau architecture in Sweden.
  • D. Hans Göran
    Hans Göran is the given first name of Göran Persson, the former Prime Minister of Sweden.
  • E. Charles Boberg
    Charles Boberg is a linguist and scholar of North American English dialects, particularly known for his work on regional variation and phonology.
  • 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: Göran Gillinger
Triple: [Göran, hasNotableBearer, Göran Gillinger]
Generated description
Göran Gillinger is a Swedish actor known for his work in film, television, and theater.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Göran Gillinger
Target entity description: Göran Gillinger is a Swedish actor known for his work in film, television, and theater.
  • A. Göran Rosenberg
    Göran Rosenberg is a Swedish journalist, author, and public intellectual known for his works on politics, history, and the Jewish experience in Sweden.
  • B. Arvid Genetz
    Arvid Genetz was a Finnish linguist, poet, and politician known for his contributions to Finno-Ugric language studies and his role in the Finnish national movement.
  • C. Ferdinand Boberg
    Ferdinand Boberg was a prominent Swedish architect of the late 19th and early 20th centuries, known for his influential contributions to national romantic and Art Nouveau architecture in Sweden.
  • D. Hans Göran
    Hans Göran is the given first name of Göran Persson, the former Prime Minister of Sweden.
  • E. Charles Boberg
    Charles Boberg is a linguist and scholar of North American English dialects, particularly known for his work on regional variation and phonology.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b795fc8190aa50ce3c7360ff83 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9881d84588190a9117064a0950ac1 completed April 10, 2026, 11:30 p.m.
NEDg Description generation batch_69d98ae8403c81908a229aa06bd0388a completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98ce9ba0c8190a7c62fa670e23705 completed April 10, 2026, 11:51 p.m.
Created at: April 6, 2026, 12:06 p.m.