Triple

T10797715
Position Surface form Disambiguated ID Type / Status
Subject Ivy Litvinov E254753 entity
Predicate birthName P65 FINISHED
Object Ivy Low
Ivy Low, later known as Ivy Litvinov, was a British-born writer and translator who became notable for her work in the Soviet Union and her marriage to Russian revolutionary Maxim Litvinov.
 E885648 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: Ivy Low | Statement: [Ivy Litvinov, birthName, Ivy Low]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ivy Low
Context triple: [Ivy Litvinov, birthName, Ivy Low]
  • A. Estella Kwan
    Estella Kwan is the mother of American figure skating champion Michelle Wingshan Kwan.
  • B. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • C. Yvonne Chan
    Yvonne Chan is the maternal grandmother of August Chan Zuckerberg, the daughter of Facebook co-founder Mark Zuckerberg and pediatrician Priscilla Chan.
  • D. Anita Chan
    Anita Chan is a prominent scholar known for her influential research on Chinese labor issues and labor rights.
  • E. Nancy Kwan
    Nancy Kwan is a pioneering Hong Kong–born actress who became an international star in the 1960s and a trailblazer for Asian representation in Hollywood and global cinema.
  • 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: Ivy Low
Triple: [Ivy Litvinov, birthName, Ivy Low]
Generated description
Ivy Low, later known as Ivy Litvinov, was a British-born writer and translator who became notable for her work in the Soviet Union and her marriage to Russian revolutionary Maxim Litvinov.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ivy Low
Target entity description: Ivy Low, later known as Ivy Litvinov, was a British-born writer and translator who became notable for her work in the Soviet Union and her marriage to Russian revolutionary Maxim Litvinov.
  • A. Estella Kwan
    Estella Kwan is the mother of American figure skating champion Michelle Wingshan Kwan.
  • B. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • C. Yvonne Chan
    Yvonne Chan is the maternal grandmother of August Chan Zuckerberg, the daughter of Facebook co-founder Mark Zuckerberg and pediatrician Priscilla Chan.
  • D. Anita Chan
    Anita Chan is a prominent scholar known for her influential research on Chinese labor issues and labor rights.
  • E. Nancy Kwan
    Nancy Kwan is a pioneering Hong Kong–born actress who became an international star in the 1960s and a trailblazer for Asian representation in Hollywood and global cinema.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73333dc4081909faa40c10bce2735 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69de566352608190ab15e3a4b690c9a5 completed April 14, 2026, 2:59 p.m.
NEDg Description generation batch_69de5eae7ab88190a0c512cfe61e3458 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de60907e1081908405b6d71adbd388 completed April 14, 2026, 3:43 p.m.
Created at: April 8, 2026, 9:17 p.m.