Triple

T12481828
Position Surface form Disambiguated ID Type / Status
Subject Pamela Evette E298327 entity
Predicate familyName P18 FINISHED
Object Evette
Evette is the surname of Pamela Evette, an American politician who has served as the lieutenant governor of South Carolina.
 E985635 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: Evette | Statement: [Pamela Evette, familyName, Evette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Evette
Context triple: [Pamela Evette, familyName, Evette]
  • A. Keoma
    Keoma is a 1976 Italian spaghetti Western film directed by Enzo G. Castellari, widely regarded as one of Franco Nero’s most iconic and atmospheric roles.
  • B. Mayte
    Mayte is a Spanish feminine given name, often used as a diminutive of María Teresa or similar compound names.
  • C. Mayte
    Mayte is the given first name of American actress Michelle Rodriguez, known for her roles in action films and the Fast & Furious franchise.
  • D. Jacobina
    Jacobina is a feminine given name, primarily used in Germanic and Scandinavian contexts, that is etymologically related to names like Jacqueline and Jacob.
  • E. Wenzelia
    Wenzelia is a genus of flowering plants in the citrus family Rutaceae, comprising shrubs or small trees native to parts of Southeast Asia and the Pacific.
  • 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: Evette
Triple: [Pamela Evette, familyName, Evette]
Generated description
Evette is the surname of Pamela Evette, an American politician who has served as the lieutenant governor of South Carolina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Evette
Target entity description: Evette is the surname of Pamela Evette, an American politician who has served as the lieutenant governor of South Carolina.
  • A. Keoma
    Keoma is a 1976 Italian spaghetti Western film directed by Enzo G. Castellari, widely regarded as one of Franco Nero’s most iconic and atmospheric roles.
  • B. Mayte
    Mayte is a Spanish feminine given name, often used as a diminutive of María Teresa or similar compound names.
  • C. Mayte
    Mayte is the given first name of American actress Michelle Rodriguez, known for her roles in action films and the Fast & Furious franchise.
  • D. Jacobina
    Jacobina is a feminine given name, primarily used in Germanic and Scandinavian contexts, that is etymologically related to names like Jacqueline and Jacob.
  • E. Wenzelia
    Wenzelia is a genus of flowering plants in the citrus family Rutaceae, comprising shrubs or small trees native to parts of Southeast Asia and the Pacific.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcef6548190a6d29375bdabd17d completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f29307c8190b024d889d45ba9f7 completed May 2, 2026, 6:15 p.m.
NEDg Description generation batch_69f6437e88c881909b7f1d55c11b0825 completed May 2, 2026, 6:33 p.m.
NED2 Entity disambiguation (via description) batch_69f644464c0c8190a8d4ea4914d32e7f completed May 2, 2026, 6:36 p.m.
Created at: April 8, 2026, 9:56 p.m.