Triple

T16008176
Position Surface form Disambiguated ID Type / Status
Subject Maggie Q E388270 entity
Predicate playedCharacter P1507 FINISHED
Object Nikita Mears
Nikita Mears is the highly skilled rogue assassin and central protagonist of the action-thriller TV series "Nikita."
E1188998 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: Nikita Mears | Statement: [Maggie Q, playedCharacter, Nikita Mears]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nikita Mears
Context triple: [Maggie Q, playedCharacter, Nikita Mears]
  • A. Nikki Alexander
    Nikki Alexander is a central forensic pathologist character in the British crime drama television series "Silent Witness."
  • B. Makenzy Doniak
    Makenzy Doniak is an American professional soccer forward known for her standout collegiate career at the University of Virginia and subsequent play in the National Women's Soccer League.
  • C. Kayla Fenech
    Kayla Fenech is the daughter of Australian former world champion boxer Jeff Fenech.
  • D. Mikaela Banes
    Mikaela Banes is a skilled, street-smart mechanic and the primary human female protagonist in the early live-action Transformers films, portrayed by Megan Fox.
  • E. Mackenzie Rosman
    Mackenzie Rosman is an American actress best known for playing Ruthie Camden on the long-running family drama series "7th Heaven."
  • 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: Nikita Mears
Triple: [Maggie Q, playedCharacter, Nikita Mears]
Generated description
Nikita Mears is the highly skilled rogue assassin and central protagonist of the action-thriller TV series "Nikita."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nikita Mears
Target entity description: Nikita Mears is the highly skilled rogue assassin and central protagonist of the action-thriller TV series "Nikita."
  • A. Nikki Alexander
    Nikki Alexander is a central forensic pathologist character in the British crime drama television series "Silent Witness."
  • B. Makenzy Doniak
    Makenzy Doniak is an American professional soccer forward known for her standout collegiate career at the University of Virginia and subsequent play in the National Women's Soccer League.
  • C. Kayla Fenech
    Kayla Fenech is the daughter of Australian former world champion boxer Jeff Fenech.
  • D. Mikaela Banes
    Mikaela Banes is a skilled, street-smart mechanic and the primary human female protagonist in the early live-action Transformers films, portrayed by Megan Fox.
  • E. Mackenzie Rosman
    Mackenzie Rosman is an American actress best known for playing Ruthie Camden on the long-running family drama series "7th Heaven."
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15800e3608190bd3e1123ccc6c326 completed April 16, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf22db3481909141ddef151d0341 completed May 10, 2026, 12:19 a.m.
NEDg Description generation batch_69ffd08186d081909b6e236768dc3cde completed May 10, 2026, 12:25 a.m.
NED2 Entity disambiguation (via description) batch_69ffd0f1914c81908c55df30a27fc0d1 completed May 10, 2026, 12:27 a.m.
Created at: April 10, 2026, 4:55 a.m.