Triple

T5140708
Position Surface form Disambiguated ID Type / Status
Subject Guy Kibbee E115943 entity
Predicate familyName P18 FINISHED
Object Kibbee
Kibbee is a surname most notably associated with American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
 E115943 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: Kibbee | Statement: [Guy Kibbee, familyName, Kibbee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kibbee
Context triple: [Guy Kibbee, familyName, Kibbee]
  • A. Guy Kibbee
    Guy Kibbee was an American character actor best known for his affable, often comical supporting roles in 1930s and 1940s Hollywood films.
  • B. Lamon
    Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
  • C. Motobu
    Motobu is a town on the northern part of Okinawa Island in Japan, known for its coastal scenery, marine attractions, and role as a regional tourist destination.
  • D. Tibbett
    Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
  • E. Kabnis
    Kabnis is a central character in Jean Toomer's modernist work "Cane," representing the struggles of a Northern-educated Black man confronting the racial and cultural realities of the rural American South.
  • 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: Kibbee
Triple: [Guy Kibbee, familyName, Kibbee]
Generated description
Kibbee is a surname most notably associated with American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kibbee
Target entity description: Kibbee is a surname most notably associated with American character actor Guy Kibbee, known for his roles in 1930s and 1940s Hollywood films.
  • A. Guy Kibbee chosen
    Guy Kibbee was an American character actor best known for his affable, often comical supporting roles in 1930s and 1940s Hollywood films.
  • B. Lamon
    Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
  • C. Motobu
    Motobu is a town on the northern part of Okinawa Island in Japan, known for its coastal scenery, marine attractions, and role as a regional tourist destination.
  • D. Tibbett
    Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
  • E. Kabnis
    Kabnis is a central character in Jean Toomer's modernist work "Cane," representing the struggles of a Northern-educated Black man confronting the racial and cultural realities of the rural American South.
  • F. None of above.

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_69bd44459a988190a772a5c2ec6a1965 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd787e5fe88190834042a73d4d9619 completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed91e4ab88190827a77b0a356b7c3 completed March 21, 2026, 5:45 p.m.
NEDg Description generation batch_69beda884bf48190a2d2b88b707609fc completed March 21, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_69bedadb77dc81909604133f25977f35 completed March 21, 2026, 5:52 p.m.
Created at: March 20, 2026, 1:43 p.m.