Triple

T3971302
Position Surface form Disambiguated ID Type / Status
Subject Autumn Sonata E92340 entity
Predicate editedBy P1954 FINISHED
Object Sylvia Ingemarsson
Sylvia Ingemarsson is a film editor best known for her work on Ingmar Bergman’s drama "Autumn Sonata."
E407148 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: Sylvia Ingemarsson | Statement: [Autumn Sonata, editedBy, Sylvia Ingemarsson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvia Ingemarsson
Context triple: [Autumn Sonata, editedBy, Sylvia Ingemarsson]
  • A. Annette Ekblom
    Annette Ekblom is an English actress known for her work in television, film, and theatre, including roles in series such as "Brookside" and "The Broker's Man."
  • B. Ingrid Carlberg
    Ingrid Carlberg is a Swedish author and journalist known for her acclaimed non-fiction works and contributions to investigative reporting.
  • C. Ylva Johansson
    Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
  • D. Marianne Dahlbäck
    Marianne Dahlbäck is a Swedish architect best known for co-designing Stockholm’s Vasa Museum, one of Scandinavia’s most visited cultural landmarks.
  • E. Åsa Larsson
    Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
  • 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: Sylvia Ingemarsson
Triple: [Autumn Sonata, editedBy, Sylvia Ingemarsson]
Generated description
Sylvia Ingemarsson is a film editor best known for her work on Ingmar Bergman’s drama "Autumn Sonata."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sylvia Ingemarsson
Target entity description: Sylvia Ingemarsson is a film editor best known for her work on Ingmar Bergman’s drama "Autumn Sonata."
  • A. Annette Ekblom
    Annette Ekblom is an English actress known for her work in television, film, and theatre, including roles in series such as "Brookside" and "The Broker's Man."
  • B. Ingrid Carlberg
    Ingrid Carlberg is a Swedish author and journalist known for her acclaimed non-fiction works and contributions to investigative reporting.
  • C. Ylva Johansson
    Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
  • D. Marianne Dahlbäck
    Marianne Dahlbäck is a Swedish architect best known for co-designing Stockholm’s Vasa Museum, one of Scandinavia’s most visited cultural landmarks.
  • E. Åsa Larsson
    Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef995d27881908b24a5b2ef57455f completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c443e208190a8bf83ec642a142e completed March 14, 2026, 11:53 a.m.
NEDg Description generation batch_69b5505592bc8190bedda7df9eef8fa7 completed March 14, 2026, 12:11 p.m.
NED2 Entity disambiguation (via description) batch_69b550e241048190aaa72504bc278c98 completed March 14, 2026, 12:13 p.m.
Created at: March 9, 2026, 3:32 p.m.