Triple

T10393969
Position Surface form Disambiguated ID Type / Status
Subject Kristina från Duvemåla E244959 entity
Predicate mainCharacter P1183 FINISHED
Object Ulrika
Ulrika is a central character in the Swedish musical "Kristina från Duvemåla," known as a strong-willed and controversial woman whose life intertwines with the emigrant community.
 E859334 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: Ulrika | Statement: [Kristina från Duvemåla, mainCharacter, Ulrika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ulrika
Context triple: [Kristina från Duvemåla, mainCharacter, Ulrika]
  • A. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • B. Ulrika Wolf-Knuts
    Ulrika Wolf-Knuts is a Finnish folklorist and academic who has served as chancellor of Åbo Akademi University.
  • C. Henrike
    Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
  • D. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • E. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • 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: Ulrika
Triple: [Kristina från Duvemåla, mainCharacter, Ulrika]
Generated description
Ulrika is a central character in the Swedish musical "Kristina från Duvemåla," known as a strong-willed and controversial woman whose life intertwines with the emigrant community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ulrika
Target entity description: Ulrika is a central character in the Swedish musical "Kristina från Duvemåla," known as a strong-willed and controversial woman whose life intertwines with the emigrant community.
  • A. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • B. Ulrika Wolf-Knuts
    Ulrika Wolf-Knuts is a Finnish folklorist and academic who has served as chancellor of Åbo Akademi University.
  • C. Henrike
    Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
  • D. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • E. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • 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_69d795c8271c81908a6b67822050c06d completed April 9, 2026, 12:04 p.m.
NEDg Description generation batch_69d7975191ac8190b32eb6cc1f5c88aa completed April 9, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d798655c7c8190a5da5ef976102285 completed April 9, 2026, 12:15 p.m.
Created at: April 6, 2026, 12:06 p.m.