Triple

T13779898
Position Surface form Disambiguated ID Type / Status
Subject Total Divas E331105 entity
Predicate features P997 FINISHED
Object Rosa Mendes
Rosa Mendes is a Canadian professional wrestler, model, and former WWE Diva best known for her tenure with WWE and appearances on the reality TV series Total Divas.
E1065180 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: Rosa Mendes | Statement: [Total Divas, features, Rosa Mendes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosa Mendes
Context triple: [Total Divas, features, Rosa Mendes]
  • A. Rosa Loy
    Rosa Loy is a contemporary German painter associated with the New Leipzig School, known for her enigmatic, dreamlike figurative works that often explore female perspectives and surreal narratives.
  • B. Matilde Andrades
    Matilde Andrades was the mother of influential American artist Jean-Michel Basquiat.
  • C. Patricia Farina
    Patricia Farina is best known as the wife of the late American actor and former Chicago police officer Dennis Farina.
  • D. Lucilla Crespin
    Lucilla Crespin is a fictional character featured in the 1923 silent drama film "The Green Goddess."
  • E. Mabel Mora
    Mabel Mora is a sharp-witted, enigmatic young woman and true-crime enthusiast who becomes one of the central amateur sleuths investigating murders in the comedy-mystery series "Only Murders in the Building."
  • 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: Rosa Mendes
Triple: [Total Divas, features, Rosa Mendes]
Generated description
Rosa Mendes is a Canadian professional wrestler, model, and former WWE Diva best known for her tenure with WWE and appearances on the reality TV series Total Divas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rosa Mendes
Target entity description: Rosa Mendes is a Canadian professional wrestler, model, and former WWE Diva best known for her tenure with WWE and appearances on the reality TV series Total Divas.
  • A. Rosa Loy
    Rosa Loy is a contemporary German painter associated with the New Leipzig School, known for her enigmatic, dreamlike figurative works that often explore female perspectives and surreal narratives.
  • B. Matilde Andrades
    Matilde Andrades was the mother of influential American artist Jean-Michel Basquiat.
  • C. Patricia Farina
    Patricia Farina is best known as the wife of the late American actor and former Chicago police officer Dennis Farina.
  • D. Lucilla Crespin
    Lucilla Crespin is a fictional character featured in the 1923 silent drama film "The Green Goddess."
  • E. Mabel Mora
    Mabel Mora is a sharp-witted, enigmatic young woman and true-crime enthusiast who becomes one of the central amateur sleuths investigating murders in the comedy-mystery series "Only Murders in the Building."
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02460a688190a27874f8d35819c7 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0e152ac8190b8d705295df4834a completed May 3, 2026, 9:40 p.m.
NEDg Description generation batch_69f7c18a032481909fc1e97883062170 completed May 3, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69f7c21231f48190ae6e2bdb2bbc0afd completed May 3, 2026, 9:45 p.m.
Created at: April 9, 2026, 10:11 p.m.