Triple

T11563881
Position Surface form Disambiguated ID Type / Status
Subject Coco Bandicoot E274205 entity
Predicate voiceActorInEnglish P83203 FINISHED
Object Kirsten Potter
Kirsten Potter is an American actress and voice actress known for her work in video games, animation, and television.
E955749 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: Kirsten Potter | Statement: [Coco Bandicoot, voiceActorInEnglish, Kirsten Potter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirsten Potter
Context triple: [Coco Bandicoot, voiceActorInEnglish, Kirsten Potter]
  • A. Kirsten Nelson
    Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
  • B. Kirsten Sheridan
    Kirsten Sheridan is an Irish film director and screenwriter known for character-driven dramas such as "August Rush" and "Disco Pigs."
  • C. Kirsten Elms
    Kirsten Elms is a screenwriter best known for co-writing the horror film "Texas Chainsaw 3D."
  • D. Kirsten Lees
    Kirsten Lees is a prominent architect and partner at Grimshaw Architects, known for her leadership on major cultural and public projects.
  • E. Julianne Potter
    Julianne Potter is the impulsive, commitment-phobic food critic who schemes to sabotage her best friend’s wedding in the romantic comedy film "My Best Friend’s Wedding."
  • 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: Kirsten Potter
Triple: [Coco Bandicoot, voiceActorInEnglish, Kirsten Potter]
Generated description
Kirsten Potter is an American actress and voice actress known for her work in video games, animation, and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kirsten Potter
Target entity description: Kirsten Potter is an American actress and voice actress known for her work in video games, animation, and television.
  • A. Kirsten Nelson
    Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
  • B. Kirsten Sheridan
    Kirsten Sheridan is an Irish film director and screenwriter known for character-driven dramas such as "August Rush" and "Disco Pigs."
  • C. Kirsten Elms
    Kirsten Elms is a screenwriter best known for co-writing the horror film "Texas Chainsaw 3D."
  • D. Kirsten Lees
    Kirsten Lees is a prominent architect and partner at Grimshaw Architects, known for her leadership on major cultural and public projects.
  • E. Julianne Potter
    Julianne Potter is the impulsive, commitment-phobic food critic who schemes to sabotage her best friend’s wedding in the romantic comedy film "My Best Friend’s Wedding."
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd321f88190a57ecaf079fbbc3f completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f457dc01ec8190a7ee3108d4d95957 completed May 1, 2026, 7:35 a.m.
NEDg Description generation batch_69f4645a7038819089d7533715f8a430 completed May 1, 2026, 8:29 a.m.
NED2 Entity disambiguation (via description) batch_69f4664ff9608190b23e29b3e5c1c326 completed May 1, 2026, 8:37 a.m.
Created at: April 8, 2026, 9:37 p.m.