Triple

T5235188
Position Surface form Disambiguated ID Type / Status
Subject Wise E118203 entity
Predicate hasNotableBearer P458 FINISHED
Object Jennifer Wise
Jennifer Wise is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Wise.
E505388 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: Jennifer Wise | Statement: [Wise, hasNotableBearer, Jennifer Wise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Wise
Context triple: [Wise, hasNotableBearer, Jennifer Wise]
  • A. Virginia Weidler
    Virginia Weidler was an American child actress of the 1930s and 1940s, best remembered for her witty supporting roles in classic Hollywood films such as "The Philadelphia Story."
  • B. Rebecca Feely
    Rebecca Feely is known as the wife of former NFL placekicker and sports commentator Jay Feely.
  • C. Corinne Kingsbury
    Corinne Kingsbury is an American television writer and producer known for creating the series "In the Dark" and "Fam."
  • D. Deborah Raffin
    Deborah Raffin was an American actress and audiobook publisher known for her film and television roles in the 1970s and 1980s and for co-founding a successful audio book company.
  • E. Victoria Strouse
    Victoria Strouse is an American screenwriter best known for co-writing Pixar's animated film "Finding Dory."
  • 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: Jennifer Wise
Triple: [Wise, hasNotableBearer, Jennifer Wise]
Generated description
Jennifer Wise is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Wise.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jennifer Wise
Target entity description: Jennifer Wise is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Wise.
  • A. Virginia Weidler
    Virginia Weidler was an American child actress of the 1930s and 1940s, best remembered for her witty supporting roles in classic Hollywood films such as "The Philadelphia Story."
  • B. Rebecca Feely
    Rebecca Feely is known as the wife of former NFL placekicker and sports commentator Jay Feely.
  • C. Corinne Kingsbury
    Corinne Kingsbury is an American television writer and producer known for creating the series "In the Dark" and "Fam."
  • D. Deborah Raffin
    Deborah Raffin was an American actress and audiobook publisher known for her film and television roles in the 1970s and 1980s and for co-founding a successful audio book company.
  • E. Victoria Strouse
    Victoria Strouse is an American screenwriter best known for co-writing Pixar's animated film "Finding Dory."
  • 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_69bd4467db0881909b3b0982df32cc8f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b064b6881909f5746f55aa422c6 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef81cca948190ab00302787367f43 completed March 21, 2026, 7:57 p.m.
NEDg Description generation batch_69befa15850481908fd414672620e0a3 completed March 21, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_69befa65a42c81908b8fe5661e9567cb completed March 21, 2026, 8:07 p.m.
Created at: March 20, 2026, 1:49 p.m.