Triple

T14567663
Position Surface form Disambiguated ID Type / Status
Subject Rose Beuret E341826 entity
Predicate givenName P17 FINISHED
Object Rose
Rose is a feminine given name of Latin origin meaning "rose" or "flower," commonly used in many European and English-speaking countries.
 E288808 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: Rose | Statement: [Rose Beuret, givenName, Rose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rose
Context triple: [Rose Beuret, givenName, Rose]
  • A. Rose
    Rose is a central character in Tommy Wiseau’s cult film "The Room," known for her manipulative relationship with the protagonist, Johnny.
  • B. Rose
    Rose is a young woman confined to a brutal Irish Magdalene asylum in the 2002 drama film "The Magdalene Sisters."
  • C. Rose
    Rose is a central character in the musical "Gypsy," known as the domineering and ambitious stage mother whose relentless drive propels much of the story’s drama.
  • D. Rose
    Rose is a person involved in an unconventional romantic relationship with Bob Gossage.
  • E. Rose
    Rose is a fictional character who serves as the intended recipient or focus of the work "Some People."
  • 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: Rose
Triple: [Rose Beuret, givenName, Rose]
Generated description
Rose is a feminine given name of Latin origin meaning "rose" or "flower," commonly used in many European and English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rose
Target entity description: Rose is a feminine given name of Latin origin meaning "rose" or "flower," commonly used in many European and English-speaking countries.
  • A. Rose chosen
    Rose is a feminine given name commonly associated with the flower and often used in English-speaking countries.
  • B. Rose
    Rose is a common English surname shared by many individuals, including the American basketball player Derrick Rose.
  • C. Rose
    Rose is a fragrance and body care line by Roger & Gallet centered on the delicate, classic scent of roses.
  • D. Rose
    Rose is a young woman confined to a brutal Irish Magdalene asylum in the 2002 drama film "The Magdalene Sisters."
  • E. Rose
    Rose is a fictional character who serves as the intended recipient or focus of the work "Some People."
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb38d89fc819086709fd3607b835f completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ac669cc819083e05620b1e8c370 completed May 8, 2026, 7:03 a.m.
NEDg Description generation batch_69fd8c5b09448190ad084746a6dd23f5 completed May 8, 2026, 7:10 a.m.
NED2 Entity disambiguation (via description) batch_69fd8d609684819090a9c3f2304f4a6a completed May 8, 2026, 7:14 a.m.
Created at: April 10, 2026, 1:23 a.m.