Triple

T1165746
Position Surface form Disambiguated ID Type / Status
Subject Nancy E24594 entity
Predicate hasRelatedName P3889 FINISHED
Object Nina
Nina is a feminine given name used in various cultures, often associated with meanings such as "little girl" or "grace."
 E109320 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: Nina | Statement: [Nancy, hasRelatedName, Nina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nina
Context triple: [Nancy, hasRelatedName, Nina]
  • A. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • B. Nora
    Nora is a feminine given name of Latin origin, often used independently or as a diminutive of names like Honora, Eleanor, or Leonora.
  • C. Sonia
    Sonia is a central female character in the romantic comedy film "Think Like a Man," whose relationships and personal growth intersect with the movie’s ensemble cast and themes about modern dating.
  • D. Sonia
    Sonia is the given name of Sonia Gandhi, an Italian-born Indian politician and former president of the Indian National Congress.
  • E. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • 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: Nina
Triple: [Nancy, hasRelatedName, Nina]
Generated description
Nina is a feminine given name used in various cultures, often associated with meanings such as "little girl" or "grace."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nina
Target entity description: Nina is a feminine given name used in various cultures, often associated with meanings such as "little girl" or "grace."
  • A. Nina chosen
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • B. Nora
    Nora is a feminine given name of Latin origin, often used independently or as a diminutive of names like Honora, Eleanor, or Leonora.
  • C. Sonia
    Sonia is a central female character in the romantic comedy film "Think Like a Man," whose relationships and personal growth intersect with the movie’s ensemble cast and themes about modern dating.
  • D. Sonia
    Sonia is the given name of Sonia Gandhi, an Italian-born Indian politician and former president of the Indian National Congress.
  • E. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccc62a88190882d8801908015a4 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde0684e4819091720c985c317671 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acde870bac8190bd1c2636fca1dc74 completed March 8, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_69acdef0bd0c81908e1eeb6851a2368d completed March 8, 2026, 2:29 a.m.
Created at: March 1, 2026, 7:45 p.m.