Triple

T6953779
Position Surface form Disambiguated ID Type / Status
Subject Star Trek: Lower Decks E161190 entity
Predicate voiceActor P1507 FINISHED
Object Tawny Newsome
Tawny Newsome is an American actress, comedian, and musician best known for her comedic roles and voice work, including starring in the animated series Star Trek: Lower Decks.
 E632058 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: Tawny Newsome | Statement: [Star Trek: Lower Decks, voiceActor, Tawny Newsome]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tawny Newsome
Context triple: [Star Trek: Lower Decks, voiceActor, Tawny Newsome]
  • A. Pattie Mallette
    Pattie Mallette is a Canadian author and film producer best known as the mother of pop singer Justin Bieber.
  • B. Pam Bryant
    Pam Bryant is an American woman best known as the mother of the late NBA superstar Kobe Bryant.
  • C. Wendy Harris
    Wendy Harris is a character known for being the mother figure in the context of the work in which she appears.
  • D. Ed Hochuli
    Ed Hochuli is a former National Football League official known for his long tenure, muscular physique, and detailed on-field explanations of penalties.
  • E. LaVonne Griffin-Valade
    LaVonne Griffin-Valade is an American public official and former auditor who serves as Oregon’s Secretary of State.
  • 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: Tawny Newsome
Triple: [Star Trek: Lower Decks, voiceActor, Tawny Newsome]
Generated description
Tawny Newsome is an American actress, comedian, and musician best known for her comedic roles and voice work, including starring in the animated series Star Trek: Lower Decks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tawny Newsome
Target entity description: Tawny Newsome is an American actress, comedian, and musician best known for her comedic roles and voice work, including starring in the animated series Star Trek: Lower Decks.
  • A. Pattie Mallette
    Pattie Mallette is a Canadian author and film producer best known as the mother of pop singer Justin Bieber.
  • B. Pam Bryant
    Pam Bryant is an American woman best known as the mother of the late NBA superstar Kobe Bryant.
  • C. Wendy Harris
    Wendy Harris is a character known for being the mother figure in the context of the work in which she appears.
  • D. Ed Hochuli
    Ed Hochuli is a former National Football League official known for his long tenure, muscular physique, and detailed on-field explanations of penalties.
  • E. LaVonne Griffin-Valade
    LaVonne Griffin-Valade is an American public official and former auditor who serves as Oregon’s Secretary of State.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dacca12481908942ba793a104cc3 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7587ee1b08190b9f53ab7df4a4a58 completed March 28, 2026, 4:26 a.m.
NEDg Description generation batch_69c75a8998308190b99a11d5aaf7436b completed March 28, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c75afddbf88190884d98e4b8a0c9eb completed March 28, 2026, 4:37 a.m.
Created at: March 27, 2026, 2:29 p.m.