Triple

T18289560
Position Surface form Disambiguated ID Type / Status
Subject Augusta Wilhelmena Fredericka Appel E438073 entity
Predicate givenName P17 FINISHED
Object Wilhelmena
Wilhelmena is a feminine given name, often used as a variant of Wilhelmina in Germanic and English-speaking contexts.
 E1316694 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: Wilhelmena | Statement: [Augusta Wilhelmena Fredericka Appel, givenName, Wilhelmena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wilhelmena
Context triple: [Augusta Wilhelmena Fredericka Appel, givenName, Wilhelmena]
  • A. Leonila
    Leonila is a feminine given name commonly used in the Philippines and other Spanish-influenced cultures.
  • B. Diana
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • C. Diana
    Diana is a renowned sculpture by Brazilian-Italian modernist artist Victor Brecheret, exemplifying his stylized, classical approach to the human figure.
  • D. Princess May
    Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
  • E. Everina
    Everina Wollstonecraft was an 18th-century English governess and writer, best known as the younger sister of feminist philosopher Mary Wollstonecraft.
  • 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: Wilhelmena
Triple: [Augusta Wilhelmena Fredericka Appel, givenName, Wilhelmena]
Generated description
Wilhelmena is a feminine given name, often used as a variant of Wilhelmina in Germanic and English-speaking contexts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wilhelmena
Target entity description: Wilhelmena is a feminine given name, often used as a variant of Wilhelmina in Germanic and English-speaking contexts.
  • A. Leonila
    Leonila is a feminine given name commonly used in the Philippines and other Spanish-influenced cultures.
  • B. Diana
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • C. Diana
    Diana is a renowned sculpture by Brazilian-Italian modernist artist Victor Brecheret, exemplifying his stylized, classical approach to the human figure.
  • D. Princess May
    Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
  • E. Everina
    Everina Wollstonecraft was an 18th-century English governess and writer, best known as the younger sister of feminist philosopher Mary Wollstonecraft.
  • 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_69d8b914530c8190b4474d862a2b2a1b completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e500fd65888190afdbb29dc60066af completed April 19, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03bb5612448190a72548b7dd7c3dc7 completed May 12, 2026, 11:44 p.m.
NEDg Description generation batch_6a03bbfa0da481908bb0e388dcbe9913 completed May 12, 2026, 11:47 p.m.
NED2 Entity disambiguation (via description) batch_6a03bd6078b88190887a32099fc31db0 completed May 12, 2026, 11:53 p.m.
Created at: April 10, 2026, 10:35 a.m.