Triple

T12125880
Position Surface form Disambiguated ID Type / Status
Subject Rose E288808 entity
Predicate hasVariant P455 FINISHED
Object Rosalyn
Rosalyn is a feminine given name, often considered a variant of Rosalind or Rose, typically associated with meanings related to "rose" and beauty.
E994172 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: Rosalyn | Statement: [Rose, hasVariant, Rosalyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosalyn
Context triple: [Rose, hasVariant, Rosalyn]
  • A. Mary Ruth
    Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
  • B. Ruth Rose
    Ruth Rose was an American screenwriter best known for co-writing the classic 1933 monster film "King Kong."
  • C. Marilynne
    Marilynne is the given name of Marilynne Robinson, the acclaimed American novelist and essayist known for works such as "Housekeeping" and the "Gilead" series.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Renee
    Renee is a feminine given name of French origin, commonly used in English- and French-speaking countries.
  • 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: Rosalyn
Triple: [Rose, hasVariant, Rosalyn]
Generated description
Rosalyn is a feminine given name, often considered a variant of Rosalind or Rose, typically associated with meanings related to "rose" and beauty.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rosalyn
Target entity description: Rosalyn is a feminine given name, often considered a variant of Rosalind or Rose, typically associated with meanings related to "rose" and beauty.
  • A. Mary Ruth
    Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
  • B. Ruth Rose
    Ruth Rose was an American screenwriter best known for co-writing the classic 1933 monster film "King Kong."
  • C. Marilynne
    Marilynne is the given name of Marilynne Robinson, the acclaimed American novelist and essayist known for works such as "Housekeeping" and the "Gilead" series.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Renee
    Renee is a feminine given name of French origin, commonly used in English- and French-speaking countries.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9157b2a9881908ec0e58cf438fce0 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6684b79c48190a663e9f5504ba20c completed May 2, 2026, 9:10 p.m.
NEDg Description generation batch_69f669527fe881909baeb84ccff506c8 completed May 2, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_69f669fe4bc48190adba50ad58b10c45 completed May 2, 2026, 9:17 p.m.
Created at: April 8, 2026, 9:49 p.m.