Triple

T15732158
Position Surface form Disambiguated ID Type / Status
Subject The Afterparty E381370 entity
Predicate executiveProducer P7225 FINISHED
Object Aubrey Lee
Aubrey Lee is a television producer best known for serving as an executive producer on the mystery-comedy series "The Afterparty."
E1180189 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: Aubrey Lee | Statement: [The Afterparty, executiveProducer, Aubrey Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aubrey Lee
Context triple: [The Afterparty, executiveProducer, Aubrey Lee]
  • A. Aubrey Woods
    Aubrey Woods was a British actor best known for his role as Bill the Candy Man in the 1971 film "Willy Wonka & the Chocolate Factory."
  • B. Aubrey Wisberg
    Aubrey Wisberg was an American screenwriter, producer, and director known for his work on mid-20th-century films, particularly in the adventure and science fiction genres.
  • C. Aubrey Haynie
    Aubrey Haynie is an American bluegrass and country fiddler and mandolinist known for his virtuosic session work and solo recordings.
  • D. Aubrey Mather
    Aubrey Mather was a British character actor known for his numerous supporting roles in films from the 1930s to the 1950s.
  • E. Aubrey Jones
    Aubrey Jones was a British Conservative politician who served in senior government roles in the mid-20th century, notably in economic and industrial affairs.
  • 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: Aubrey Lee
Triple: [The Afterparty, executiveProducer, Aubrey Lee]
Generated description
Aubrey Lee is a television producer best known for serving as an executive producer on the mystery-comedy series "The Afterparty."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Aubrey Lee
Target entity description: Aubrey Lee is a television producer best known for serving as an executive producer on the mystery-comedy series "The Afterparty."
  • A. Aubrey Woods
    Aubrey Woods was a British actor best known for his role as Bill the Candy Man in the 1971 film "Willy Wonka & the Chocolate Factory."
  • B. Aubrey Wisberg
    Aubrey Wisberg was an American screenwriter, producer, and director known for his work on mid-20th-century films, particularly in the adventure and science fiction genres.
  • C. Aubrey Haynie
    Aubrey Haynie is an American bluegrass and country fiddler and mandolinist known for his virtuosic session work and solo recordings.
  • D. Aubrey Mather
    Aubrey Mather was a British character actor known for his numerous supporting roles in films from the 1930s to the 1950s.
  • E. Aubrey Jones
    Aubrey Jones was a British Conservative politician who served in senior government roles in the mid-20th century, notably in economic and industrial affairs.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd3614481908b2694b1d3550058 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa129a6448190affdee9d0b1362bc completed May 9, 2026, 9:03 p.m.
NEDg Description generation batch_69ffa417ee248190808b0fecfb58d705 completed May 9, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69ffa5372f248190827cdc4985fee1ef completed May 9, 2026, 9:20 p.m.
Created at: April 10, 2026, 4:46 a.m.