Triple

T17488219
Position Surface form Disambiguated ID Type / Status
Subject Elza Maia Costa de Oliveira E425829 entity
Predicate givenName P17 FINISHED
Object Elza
Elza is a feminine given name commonly used in Portuguese- and Spanish-speaking countries, often as a variant of Elsa.
 E1271458 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: Elza | Statement: [Elza Maia Costa de Oliveira, givenName, Elza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elza
Context triple: [Elza Maia Costa de Oliveira, givenName, Elza]
  • A. Elsy
    Elsy is a given name, typically used as a variant spelling of the name Elsie.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Lélia
    Lélia is a philosophical and romantic novel by George Sand that explores themes of female desire, existential doubt, and social constraint in 19th-century France.
  • D. Eliana
    Eliana is a feminine given name of Hebrew and Latin origin, often interpreted to mean "God has answered" or "my God has answered."
  • E. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • 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: Elza
Triple: [Elza Maia Costa de Oliveira, givenName, Elza]
Generated description
Elza is a feminine given name commonly used in Portuguese- and Spanish-speaking countries, often as a variant of Elsa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elza
Target entity description: Elza is a feminine given name commonly used in Portuguese- and Spanish-speaking countries, often as a variant of Elsa.
  • A. Elsy
    Elsy is a given name, typically used as a variant spelling of the name Elsie.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Lélia
    Lélia is a philosophical and romantic novel by George Sand that explores themes of female desire, existential doubt, and social constraint in 19th-century France.
  • D. Eliana
    Eliana is a feminine given name of Hebrew and Latin origin, often interpreted to mean "God has answered" or "my God has answered."
  • E. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451d376708190a97804529174eaf2 completed April 19, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01c1fe58c88190af53de4e32869075 completed May 11, 2026, 11:48 a.m.
NEDg Description generation batch_6a01c2b9731481908250935ea31ed0e9 completed May 11, 2026, 11:51 a.m.
NED2 Entity disambiguation (via description) batch_6a01c36efec0819082777c41218a3150 completed May 11, 2026, 11:54 a.m.
Created at: April 10, 2026, 5:48 a.m.