Triple

T13180454
Position Surface form Disambiguated ID Type / Status
Subject Ursula E313707 entity
Predicate hasVariant P455 FINISHED
Object Uršula
Uršula is a given name, commonly used in various European countries as a variant of the name Ursula.
E1029534 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: Uršula | Statement: [Ursula, hasVariant, Uršula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uršula
Context triple: [Ursula, hasVariant, Uršula]
  • A. Gertrudis
    Gertrudis is a passionate and rebellious sister in "Like Water for Chocolate" whose fiery nature and unconventional choices challenge her family's strict traditions.
  • B. Violanta
    Violanta is a one-act opera by Erich Wolfgang Korngold, known for its lush late-Romantic score and psychologically intense drama set in Renaissance Venice.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Margareta
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • E. 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.
  • 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: Uršula
Triple: [Ursula, hasVariant, Uršula]
Generated description
Uršula is a given name, commonly used in various European countries as a variant of the name Ursula.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Uršula
Target entity description: Uršula is a given name, commonly used in various European countries as a variant of the name Ursula.
  • A. Gertrudis
    Gertrudis is a passionate and rebellious sister in "Like Water for Chocolate" whose fiery nature and unconventional choices challenge her family's strict traditions.
  • B. Violanta
    Violanta is a one-act opera by Erich Wolfgang Korngold, known for its lush late-Romantic score and psychologically intense drama set in Renaissance Venice.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Margareta
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • E. 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.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c490ed081908ea54edb25c3de90 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff116f1c819097e4c53cd1411d78 completed May 3, 2026, 7:53 a.m.
NEDg Description generation batch_69f7013a368c8190a768f837f6551f5b completed May 3, 2026, 8:03 a.m.
NED2 Entity disambiguation (via description) batch_69f70386bf008190b984c81103326a67 completed May 3, 2026, 8:12 a.m.
Created at: April 9, 2026, 9:14 p.m.