Triple

T12768917
Position Surface form Disambiguated ID Type / Status
Subject A Teacher (2013 film) E305195 entity
Predicate producer P490 FINISHED
Object Kimberly Parker
Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
E1128669 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: Kimberly Parker | Statement: [A Teacher (2013 film), producer, Kimberly Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimberly Parker
Context triple: [A Teacher (2013 film), producer, Kimberly Parker]
  • A. Nicole Parker
    Nicole Parker is an American actress and comedian best known for her sketch work on MADtv and roles in parody films.
  • B. Carol Parker
    Carol Parker is best known as the wife of Marlon Jackson, a member of the famed Jackson family and former singer of The Jackson 5.
  • C. Kimberly Reese
    Kimberly Reese is a diligent, ambitious college student and close friend of Whitley Gilbert on the sitcom "A Different World," known for her academic drive and grounded personality.
  • D. Jolene Parker
    Jolene Parker is a fictional character portrayed by actress Rachel Brosnahan.
  • E. Christie Parker
    Christie Parker is a fictional character played by actress Jennifer Crystal Foley, best known from her work in American television.
  • 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: Kimberly Parker
Triple: [A Teacher (2013 film), producer, Kimberly Parker]
Generated description
Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kimberly Parker
Target entity description: Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
  • A. Nicole Parker
    Nicole Parker is an American actress and comedian best known for her sketch work on MADtv and roles in parody films.
  • B. Carol Parker
    Carol Parker is best known as the wife of Marlon Jackson, a member of the famed Jackson family and former singer of The Jackson 5.
  • C. Kimberly Reese
    Kimberly Reese is a diligent, ambitious college student and close friend of Whitley Gilbert on the sitcom "A Different World," known for her academic drive and grounded personality.
  • D. Jolene Parker
    Jolene Parker is a fictional character portrayed by actress Rachel Brosnahan.
  • E. Christie Parker
    Christie Parker is a fictional character played by actress Jennifer Crystal Foley, best known from her work in American television.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df3b2f88190b37b696400178795 completed April 10, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e70dc788190850278a40a5a62e4 completed May 9, 2026, 12:23 a.m.
NEDg Description generation batch_69fe803875988190a4786db4ae0b0cbb completed May 9, 2026, 12:30 a.m.
NED2 Entity disambiguation (via description) batch_69fe80be100481908dcf07b683fc1411 completed May 9, 2026, 12:33 a.m.
Created at: April 9, 2026, 5:28 p.m.