Triple

T16228815
Position Surface form Disambiguated ID Type / Status
Subject Out for Justice E393925 entity
Predicate starring P1507 FINISHED
Object Jo Champa
Jo Champa is an Italian-American actress and former fashion model known for her film and television roles in the 1980s and 1990s.
 E1200875 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: Jo Champa | Statement: [Out for Justice, starring, Jo Champa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jo Champa
Context triple: [Out for Justice, starring, Jo Champa]
  • A. Kieu Chinh
    Kieu Chinh is a Vietnamese-American actress best known internationally for her role in the film adaptation of Amy Tan’s novel "The Joy Luck Club."
  • B. Dang Bich Ha
    Dang Bich Ha is best known as the wife of Vietnamese General Vo Nguyen Giap, a prominent military leader in Vietnam’s 20th-century history.
  • C. Yolande Ngo Thi Hoang Lien
    Yolande Ngo Thi Hoang Lien is best known as the wife of South African writer and anti-apartheid activist Breyten Breytenbach.
  • D. Na Kim
    Na Kim is a contemporary book cover designer and artist known for her bold, minimalist, and concept-driven visual work.
  • E. Kao Kim Hourn
    Kao Kim Hourn is a Cambodian diplomat and academic who serves as the Secretary-General of the Association of Southeast Asian Nations (ASEAN).
  • 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: Jo Champa
Triple: [Out for Justice, starring, Jo Champa]
Generated description
Jo Champa is an Italian-American actress and former fashion model known for her film and television roles in the 1980s and 1990s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jo Champa
Target entity description: Jo Champa is an Italian-American actress and former fashion model known for her film and television roles in the 1980s and 1990s.
  • A. Kieu Chinh
    Kieu Chinh is a Vietnamese-American actress best known internationally for her role in the film adaptation of Amy Tan’s novel "The Joy Luck Club."
  • B. Dang Bich Ha
    Dang Bich Ha is best known as the wife of Vietnamese General Vo Nguyen Giap, a prominent military leader in Vietnam’s 20th-century history.
  • C. Yolande Ngo Thi Hoang Lien
    Yolande Ngo Thi Hoang Lien is best known as the wife of South African writer and anti-apartheid activist Breyten Breytenbach.
  • D. Na Kim
    Na Kim is a contemporary book cover designer and artist known for her bold, minimalist, and concept-driven visual work.
  • E. Kao Kim Hourn
    Kao Kim Hourn is a Cambodian diplomat and academic who serves as the Secretary-General of the Association of Southeast Asian Nations (ASEAN).
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e23d2889688190ac04e4e9479cabf4 completed April 17, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00079e83f08190a260751fd8b55eef completed May 10, 2026, 4:20 a.m.
NEDg Description generation batch_6a00089a498c819092685d13f975e7cd completed May 10, 2026, 4:24 a.m.
NED2 Entity disambiguation (via description) batch_6a0009042b288190b3a756354c04dfd3 completed May 10, 2026, 4:26 a.m.
Created at: April 10, 2026, 5:03 a.m.