Triple

T14732241
Position Surface form Disambiguated ID Type / Status
Subject Keith Neudecker E346103 entity
Predicate relationshipWith P10260 FINISHED
Object Nina unclear NED1 NE FINISHED

How this triple was built (2 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: [Keith Neudecker, relationshipWith, Nina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nina
Context triple: [Keith Neudecker, relationshipWith, 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. Nina
    Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
  • C. Nina
    Nina is a central character in the British cult film "Human Traffic," which explores the lives and clubbing culture of young people in Cardiff.
  • D. Nina
    Nina is a biographical drama film written and directed by Cynthia Mort that portrays the life and struggles of legendary musician Nina Simone.
  • E. Nita
    Nita is a feminine given name commonly used as a shortened or affectionate form of longer names such as Juanita.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (3 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec26311c8819093a81ff0fa43b33b completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24ac17888190bda346df75d37620 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:29 a.m.