Triple

T5381939
Position Surface form Disambiguated ID Type / Status
Subject Chen E113104 entity
Predicate hasVariant P455 FINISHED
Object Tran
Tran is a personal name, commonly used as both a given name and surname in various cultures, particularly in East and Southeast Asia.
 E516416 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: Tran | Statement: [Chen, hasVariant, Tran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tran
Context triple: [Chen, hasVariant, Tran]
  • A. Transtu
    Transtu is the public transport authority in Tunis responsible for operating the city’s metro and other urban transit services.
  • B. Tran Ho
    Tran Ho is a Vietnamese American physician best known as the wife of comedian and actor Ken Jeong, whose medical career and battle with breast cancer have been publicly discussed by her husband.
  • C. Thieu
    Thieu is the family name of Nguyen Van Thieu, the South Vietnamese general and president during the Vietnam War.
  • D. Quyen Tran
    Quyen Tran is an American cinematographer known for her visually expressive work on independent films and character-driven stories.
  • E. Tung Thanh Tran
    Tung Thanh Tran is an actor best known for his role in the 1987 war-comedy film "Good Morning, Vietnam."
  • 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: Tran
Triple: [Chen, hasVariant, Tran]
Generated description
Tran is a personal name, commonly used as both a given name and surname in various cultures, particularly in East and Southeast Asia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tran
Target entity description: Tran is a personal name, commonly used as both a given name and surname in various cultures, particularly in East and Southeast Asia.
  • A. Transtu
    Transtu is the public transport authority in Tunis responsible for operating the city’s metro and other urban transit services.
  • B. Tran Ho
    Tran Ho is a Vietnamese American physician best known as the wife of comedian and actor Ken Jeong, whose medical career and battle with breast cancer have been publicly discussed by her husband.
  • C. Thieu
    Thieu is the family name of Nguyen Van Thieu, the South Vietnamese general and president during the Vietnam War.
  • D. Quyen Tran
    Quyen Tran is an American cinematographer known for her visually expressive work on independent films and character-driven stories.
  • E. Tung Thanh Tran
    Tung Thanh Tran is an actor best known for his role in the 1987 war-comedy film "Good Morning, Vietnam."
  • 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_69bd4436a1988190af18dcff7fd306b4 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd86d163f88190939638d44fcb24a7 completed March 20, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf294cb9288190ab1400dae18332de completed March 21, 2026, 11:27 p.m.
NEDg Description generation batch_69bf2a23ba1881909ddc549728bbc2d3 completed March 21, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_69bf2e6d5f9081908327dff0058241f0 completed March 21, 2026, 11:49 p.m.
Created at: March 20, 2026, 2:03 p.m.