Triple

T15008795
Position Surface form Disambiguated ID Type / Status
Subject Franklin & Bash E377780 entity
Predicate character P662 FINISHED
Object Rachel King
Rachel King is a fictional attorney who appears as a recurring character in the legal comedy-drama television series "Franklin & Bash."
E1132199 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: Rachel King | Statement: [Franklin & Bash, character, Rachel King]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel King
Context triple: [Franklin & Bash, character, Rachel King]
  • A. Nina King
    Nina King is an American college athletics administrator who serves as the athletic director at Duke University, overseeing the university’s sports programs.
  • B. Jessica King
    Jessica King is a character in the supernatural thriller film "The Gift," involved in the mysterious events surrounding a small-town community.
  • C. Alison King
    Alison King is a British actress best known for her long-running role as Carla Connor in the television soap opera "Coronation Street."
  • D. Tara King
    Tara King is a fictional British secret agent and one of John Steed’s partners in the 1960s television series "The Avengers."
  • E. Alyce King
    Alyce King was an American singer best known as one of the King Sisters, a popular vocal group active in the mid-20th century.
  • 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: Rachel King
Triple: [Franklin & Bash, character, Rachel King]
Generated description
Rachel King is a fictional attorney who appears as a recurring character in the legal comedy-drama television series "Franklin & Bash."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rachel King
Target entity description: Rachel King is a fictional attorney who appears as a recurring character in the legal comedy-drama television series "Franklin & Bash."
  • A. Nina King
    Nina King is an American college athletics administrator who serves as the athletic director at Duke University, overseeing the university’s sports programs.
  • B. Jessica King
    Jessica King is a character in the supernatural thriller film "The Gift," involved in the mysterious events surrounding a small-town community.
  • C. Alison King
    Alison King is a British actress best known for her long-running role as Carla Connor in the television soap opera "Coronation Street."
  • D. Tara King
    Tara King is a fictional British secret agent and one of John Steed’s partners in the 1960s television series "The Avengers."
  • E. Alyce King
    Alyce King was an American singer best known as one of the King Sisters, a popular vocal group active in the mid-20th century.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded73348d4819091d9e7f1b0fed822 completed April 15, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe96a52bb08190961e3f18d751fe2a completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe98bf505c819089740180a763db34 completed May 9, 2026, 2:15 a.m.
NED2 Entity disambiguation (via description) batch_69fe9aab47888190812ff9732380e124 completed May 9, 2026, 2:23 a.m.
Created at: April 10, 2026, 2:55 a.m.