Triple

T621889
Position Surface form Disambiguated ID Type / Status
Subject Bill Murray E14530 entity
Predicate spouse P13 FINISHED
Object Jennifer Butler
Jennifer Butler was an American costume designer best known for her long-term relationship and marriage to actor Bill Murray.
E83907 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 Butler | Statement: [Bill Murray, spouse, Jennifer Butler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Butler
Context triple: [Bill Murray, spouse, Jennifer Butler]
  • A. Anna Beth Sully
    Anna Beth Sully was the first wife of silent film star Douglas Fairbanks, whom she married before his rise to Hollywood fame.
  • B. Lauren Daniels
    Lauren Daniels is a fictional character from the American prime-time television soap opera "Falcon Crest."
  • C. Jody Allen
    Jody Allen is an American businesswoman and philanthropist, co-founder of Vulcan Inc. and sister of the late Microsoft co-founder Paul Allen.
  • D. Martha Tedeschi
    Martha Tedeschi is an American art historian and museum leader known for her scholarship on works on paper and for heading major art institutions.
  • E. Elissa Leonard
    Elissa Leonard is an American filmmaker and producer known for her work in documentary and independent film, as well as for being married to Federal Reserve Chair Jerome H. Powell.
  • 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 Butler
Triple: [Bill Murray, spouse, Jennifer Butler]
Generated description
Jennifer Butler was an American costume designer best known for her long-term relationship and marriage to actor Bill Murray.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jennifer Butler
Target entity description: Jennifer Butler was an American costume designer best known for her long-term relationship and marriage to actor Bill Murray.
  • A. Anna Beth Sully
    Anna Beth Sully was the first wife of silent film star Douglas Fairbanks, whom she married before his rise to Hollywood fame.
  • B. Lauren Daniels
    Lauren Daniels is a fictional character from the American prime-time television soap opera "Falcon Crest."
  • C. Jody Allen
    Jody Allen is an American businesswoman and philanthropist, co-founder of Vulcan Inc. and sister of the late Microsoft co-founder Paul Allen.
  • D. Martha Tedeschi
    Martha Tedeschi is an American art historian and museum leader known for her scholarship on works on paper and for heading major art institutions.
  • E. Elissa Leonard
    Elissa Leonard is an American filmmaker and producer known for her work in documentary and independent film, as well as for being married to Federal Reserve Chair Jerome H. Powell.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e402d9c8190936896e3ebb6edc5 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc91ff30819095a00852c3e2dfae completed March 2, 2026, 6:53 p.m.
NEDg Description generation batch_69a5de26ff1081908a60b55a1deab804 completed March 2, 2026, 6:59 p.m.
NED2 Entity disambiguation (via description) batch_69a5ff1ac6f481909915fd5b2e648558 completed March 2, 2026, 9:20 p.m.
Created at: March 1, 2026, 7:35 p.m.