Triple

T9914626
Position Surface form Disambiguated ID Type / Status
Subject Reinhardt E185835 entity
Predicate hasNotableBearer P458 FINISHED
Object Gina Reinhardt
Gina Reinhardt is a notable individual associated with the surname Reinhardt, recognized as a distinguished bearer of that name.
 E833373 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: Gina Reinhardt | Statement: [Reinhardt, hasNotableBearer, Gina Reinhardt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gina Reinhardt
Context triple: [Reinhardt, hasNotableBearer, Gina Reinhardt]
  • A. Gina Ravera
    Gina Ravera is an American actress known for her roles in television series such as "The Closer" and "ER" as well as various film appearances.
  • B. Gina Schock
    Gina Schock is an American drummer best known as the powerhouse behind the pioneering all-female rock band The Go-Go’s.
  • C. Gina Ruberti
    Gina Ruberti was the wife of Bruno Mussolini, the son of Italian dictator Benito Mussolini.
  • D. Gina Wendkos
    Gina Wendkos is an American screenwriter best known for adapting Meg Cabot’s novel into the hit teen film "The Princess Diaries" and writing several other popular romantic comedies.
  • E. Lisa Eilbacher
    Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
  • 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: Gina Reinhardt
Triple: [Reinhardt, hasNotableBearer, Gina Reinhardt]
Generated description
Gina Reinhardt is a notable individual associated with the surname Reinhardt, recognized as a distinguished bearer of that name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gina Reinhardt
Target entity description: Gina Reinhardt is a notable individual associated with the surname Reinhardt, recognized as a distinguished bearer of that name.
  • A. Gina Ravera
    Gina Ravera is an American actress known for her roles in television series such as "The Closer" and "ER" as well as various film appearances.
  • B. Gina Schock
    Gina Schock is an American drummer best known as the powerhouse behind the pioneering all-female rock band The Go-Go’s.
  • C. Gina Ruberti
    Gina Ruberti was the wife of Bruno Mussolini, the son of Italian dictator Benito Mussolini.
  • D. Gina Wendkos
    Gina Wendkos is an American screenwriter best known for adapting Meg Cabot’s novel into the hit teen film "The Princess Diaries" and writing several other popular romantic comedies.
  • E. Lisa Eilbacher
    Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53ba1ac8190ba655133b81596d7 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2578390888190b60f3962aec37b2d completed April 5, 2026, 12:37 p.m.
NEDg Description generation batch_69d25889b0f08190a28c5401417fe3cc completed April 5, 2026, 12:41 p.m.
NED2 Entity disambiguation (via description) batch_69d25977ab988190969ed8ff8eb53ddd completed April 5, 2026, 12:45 p.m.
Created at: March 30, 2026, 8:41 p.m.