Triple

T14645998
Position Surface form Disambiguated ID Type / Status
Subject Edgar Bergen E343849 entity
Predicate parent P120 FINISHED
Object Nilla Svensdotter
Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
E1111554 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: Nilla Svensdotter | Statement: [Edgar Bergen, parent, Nilla Svensdotter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nilla Svensdotter
Context triple: [Edgar Bergen, parent, Nilla Svensdotter]
  • A. 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.
  • B. Stina Lindgren
    Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
  • C. 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.
  • D. Sylvia Ingemarsson
    Sylvia Ingemarsson is a film editor best known for her work on Ingmar Bergman’s drama "Autumn Sonata."
  • E. Margareta Wästberg
    Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
  • 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: Nilla Svensdotter
Triple: [Edgar Bergen, parent, Nilla Svensdotter]
Generated description
Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nilla Svensdotter
Target entity description: Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
  • A. 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.
  • B. Stina Lindgren
    Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
  • C. 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.
  • D. Sylvia Ingemarsson
    Sylvia Ingemarsson is a film editor best known for her work on Ingmar Bergman’s drama "Autumn Sonata."
  • E. Margareta Wästberg
    Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5d5d05481908dbb23392c05d23b completed May 8, 2026, 12:23 p.m.
NEDg Description generation batch_69fdd74cc4048190bae5f75d922c9618 completed May 8, 2026, 12:30 p.m.
NED2 Entity disambiguation (via description) batch_69fdd7bd20748190b9145ef14ce2759b completed May 8, 2026, 12:31 p.m.
Created at: April 10, 2026, 1:26 a.m.