Triple

T1004242
Position Surface form Disambiguated ID Type / Status
Subject Whitney Young E21672 entity
Predicate familyName P18 FINISHED
Object Young
Young is a common English surname borne by numerous notable individuals across diverse fields such as politics, civil rights, science, and the arts.
 E117890 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: Young | Statement: [Whitney Young, familyName, Young]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Young
Context triple: [Whitney Young, familyName, Young]
  • A. Young
    Young is a regional town in New South Wales, Australia, historically known for its gold rush heritage and cherry production.
  • B. Young Adult
    Young Adult is a 2011 dark comedy-drama film directed by Jason Reitman and written by Diablo Cody, starring Charlize Theron as a troubled writer who returns to her hometown.
  • C. Junior
    Junior is a 1994 comedy film in which Arnold Schwarzenegger plays a scientist who becomes pregnant as part of an experimental fertility project.
  • D. Junior
    Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
  • E. Young Fashion
    Young Fashion is a central character in the work "The Relapse," around whom much of the story’s action and development revolves.
  • 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: Young
Triple: [Whitney Young, familyName, Young]
Generated description
Young is a common English surname borne by numerous notable individuals across diverse fields such as politics, civil rights, science, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Young
Target entity description: Young is a common English surname borne by numerous notable individuals across diverse fields such as politics, civil rights, science, and the arts.
  • A. Young
    Young is a regional town in New South Wales, Australia, historically known for its gold rush heritage and cherry production.
  • B. Young Adult
    Young Adult is a 2011 dark comedy-drama film directed by Jason Reitman and written by Diablo Cody, starring Charlize Theron as a troubled writer who returns to her hometown.
  • C. Junior
    Junior is a 1994 comedy film in which Arnold Schwarzenegger plays a scientist who becomes pregnant as part of an experimental fertility project.
  • D. Junior
    Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
  • E. Young Fashion
    Young Fashion is a central character in the work "The Relapse," around whom much of the story’s action and development revolves.
  • 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_69a493c53e648190ae8cb76c433fd9a7 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4ff614081909478500ada1f5059 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a1ecddc8190b954d16c6e269498 completed March 7, 2026, 1:37 p.m.
NEDg Description generation batch_69ac2a8dd818819088e6140e9a12594b completed March 7, 2026, 1:39 p.m.
NED2 Entity disambiguation (via description) batch_69ac2af2efd88190b1da673aa3ead5fd completed March 7, 2026, 1:41 p.m.
Created at: March 1, 2026, 7:41 p.m.