Triple

T15246998
Position Surface form Disambiguated ID Type / Status
Subject Susanna E364408 entity
Predicate hasVariant P455 FINISHED
Object Susana
Susana is a feminine given name used in various cultures, often considered a variant of Susanna and associated with meanings related to "lily."
 E1145643 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: Susana | Statement: [Susanna, hasVariant, Susana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Susana
Context triple: [Susanna, hasVariant, Susana]
  • A. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • B. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • C. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • D. Rosa Elena
    Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
  • E. Graciela
    Graciela is a feminine given name of Spanish origin, often considered a variant of Graziella and related to the concept of grace.
  • 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: Susana
Triple: [Susanna, hasVariant, Susana]
Generated description
Susana is a feminine given name used in various cultures, often considered a variant of Susanna and associated with meanings related to "lily."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Susana
Target entity description: Susana is a feminine given name used in various cultures, often considered a variant of Susanna and associated with meanings related to "lily."
  • A. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • B. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • C. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • D. Rosa Elena
    Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
  • E. Graciela
    Graciela is a feminine given name of Spanish origin, often considered a variant of Graziella and related to the concept of grace.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f4f9d48190b96a7e0c6993cd69 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd491cd881908bad9660af9b6b8f completed May 9, 2026, 7:07 a.m.
NEDg Description generation batch_69fedf6ee3f081909553078cd3e9d243 completed May 9, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69fee0016a088190ad87268e035f677e completed May 9, 2026, 7:19 a.m.
Created at: April 10, 2026, 3:13 a.m.