Triple

T13345580
Position Surface form Disambiguated ID Type / Status
Subject Gunilla Risberg E317939 entity
Predicate givenName P17 FINISHED
Object Gunilla
Gunilla is a Scandinavian female given name, particularly common in Sweden and other Nordic countries.
E1035675 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: Gunilla | Statement: [Gunilla Risberg, givenName, Gunilla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gunilla
Context triple: [Gunilla Risberg, givenName, Gunilla]
  • A. Gunnel
    Gunnel is a Scandinavian feminine given name, particularly common in Sweden.
  • B. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • C. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • D. 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.
  • E. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • 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: Gunilla
Triple: [Gunilla Risberg, givenName, Gunilla]
Generated description
Gunilla is a Scandinavian female given name, particularly common in Sweden and other Nordic countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gunilla
Target entity description: Gunilla is a Scandinavian female given name, particularly common in Sweden and other Nordic countries.
  • A. Gunnel
    Gunnel is a Scandinavian feminine given name, particularly common in Sweden.
  • B. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • C. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • D. 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.
  • E. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e89c65c819093f3bea11d6073c5 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f439b3c8190b35fd4d097d65068 completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f7204ac36c8190a04e921442489e9c completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f7221887208190ac98945a023bc496 completed May 3, 2026, 10:23 a.m.
Created at: April 9, 2026, 9:31 p.m.