Triple

T13599917
Position Surface form Disambiguated ID Type / Status
Subject Onika Tanya Maraj E324915 entity
Predicate hasAlterEgo P39 FINISHED
Object Nicki Lewinsky E324928 NE FINISHED

How this triple was built (2 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: Nicki Lewinsky | Statement: [Onika Tanya Maraj, hasAlterEgo, Nicki Lewinsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicki Lewinsky
Context triple: [Onika Tanya Maraj, hasAlterEgo, Nicki Lewinsky]
  • A. Nicki Lewinsky chosen
    Nicki Lewinsky is one of Nicki Minaj’s provocative alter egos, often associated with her more sexually explicit and bold lyrical persona.
  • B. Monica Lewinsky
    Monica Lewinsky is an American activist, writer, and former White House intern best known for her involvement in a 1990s political scandal with President Bill Clinton and her later work against cyberbullying and public shaming.
  • C. Bernard Lewinsky
    Bernard Lewinsky is an American oncologist and photographer best known as the father of Monica Lewinsky.
  • D. Linda Tripp
    Linda Tripp was a former U.S. civil servant whose secret recordings of Monica Lewinsky’s conversations with her played a central role in the impeachment of President Bill Clinton.
  • E. Janet Hill
    Janet Hill is known as the former wife of Apple co-founder Steve Wozniak.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0795acc8190a08667ab9dcb0d44 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bcc1ed88190bbf6c83001703b84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.