Triple

T13222108
Position Surface form Disambiguated ID Type / Status
Subject Breaker High E314779 entity
Predicate hasCastMember P2308 FINISHED
Object Wendi Kenya
Wendi Kenya is an actress best known for her role on the teen comedy-drama television series "Breaker High."
E1027894 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: Wendi Kenya | Statement: [Breaker High, hasCastMember, Wendi Kenya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wendi Kenya
Context triple: [Breaker High, hasCastMember, Wendi Kenya]
  • A. Wendi
    Wendi is the first name of American actress and comedian Wendi McLendon-Covey, known for her roles in "Bridesmaids" and the TV series "The Goldbergs."
  • B. Wambisa
    Wambisa is an indigenous people and language group of the Amazonian region of northern Peru, known for their distinct cultural traditions and Jivaroan linguistic heritage.
  • C. Wendy Gazelle
    Wendy Gazelle is an American actress known for her work in film and television during the 1990s, including a role in the tech-thriller genre.
  • D. Lwena
    Lwena is a Bantu language spoken primarily by the Luena (Lwena) people in parts of Angola and neighboring regions of Central Africa.
  • E. Edwena
    Edwena is a feminine given name, used as an alternative spelling of Edwina.
  • 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: Wendi Kenya
Triple: [Breaker High, hasCastMember, Wendi Kenya]
Generated description
Wendi Kenya is an actress best known for her role on the teen comedy-drama television series "Breaker High."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wendi Kenya
Target entity description: Wendi Kenya is an actress best known for her role on the teen comedy-drama television series "Breaker High."
  • A. Wendi
    Wendi is the first name of American actress and comedian Wendi McLendon-Covey, known for her roles in "Bridesmaids" and the TV series "The Goldbergs."
  • B. Wambisa
    Wambisa is an indigenous people and language group of the Amazonian region of northern Peru, known for their distinct cultural traditions and Jivaroan linguistic heritage.
  • C. Wendy Gazelle
    Wendy Gazelle is an American actress known for her work in film and television during the 1990s, including a role in the tech-thriller genre.
  • D. Lwena
    Lwena is a Bantu language spoken primarily by the Luena (Lwena) people in parts of Angola and neighboring regions of Central Africa.
  • E. Edwena
    Edwena is a feminine given name, used as an alternative spelling of Edwina.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf74d708190a61d8ad938653b06 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff24be9881908b96f3e72325e55f completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f7001924d48190af7d430cb258409a completed May 3, 2026, 7:58 a.m.
NED2 Entity disambiguation (via description) batch_69f700cfb43881909c903ec12b15065a completed May 3, 2026, 8:01 a.m.
Created at: April 9, 2026, 9:18 p.m.