Triple

T3982766
Position Surface form Disambiguated ID Type / Status
Subject Behrens E86796 entity
Predicate hasNotableBearer P458 FINISHED
Object Katia Behrens
Katia Behrens is a notable individual who bears the surname Behrens, recognized for her significance among people with that name.
E403377 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: Katia Behrens | Statement: [Behrens, hasNotableBearer, Katia Behrens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katia Behrens
Context triple: [Behrens, hasNotableBearer, Katia Behrens]
  • A. Katia Winter
    Katia Winter is a Swedish actress best known for her roles in television series such as Sleepy Hollow and Dexter.
  • B. Katia Mann
    Katia Mann was a German intellectual and the wife and close confidante of Nobel Prize–winning author Thomas Mann, known for her significant influence on his life and work.
  • C. Marianne Tromlitz
    Marianne Tromlitz was the mother of the renowned Romantic-era pianist and composer Clara Schumann.
  • D. Olga von Velten
    Olga von Velten was the second wife of renowned German physicist and physiologist Hermann von Helmholtz, with whom she was associated in late 19th-century German intellectual society.
  • E. Felicia Minei Behr
    Felicia Minei Behr is an American television producer best known for her influential work in daytime soap operas.
  • 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: Katia Behrens
Triple: [Behrens, hasNotableBearer, Katia Behrens]
Generated description
Katia Behrens is a notable individual who bears the surname Behrens, recognized for her significance among people with that name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Katia Behrens
Target entity description: Katia Behrens is a notable individual who bears the surname Behrens, recognized for her significance among people with that name.
  • A. Katia Winter
    Katia Winter is a Swedish actress best known for her roles in television series such as Sleepy Hollow and Dexter.
  • B. Katia Mann
    Katia Mann was a German intellectual and the wife and close confidante of Nobel Prize–winning author Thomas Mann, known for her significant influence on his life and work.
  • C. Marianne Tromlitz
    Marianne Tromlitz was the mother of the renowned Romantic-era pianist and composer Clara Schumann.
  • D. Olga von Velten
    Olga von Velten was the second wife of renowned German physicist and physiologist Hermann von Helmholtz, with whom she was associated in late 19th-century German intellectual society.
  • E. Felicia Minei Behr
    Felicia Minei Behr is an American television producer best known for her influential work in daytime soap operas.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9dd351c81909605bc2605f541e1 completed March 9, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b540257c188190899b00bf1d0247d2 completed March 14, 2026, 11:01 a.m.
NEDg Description generation batch_69b54111e5188190ab8ec23124c22981 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b54193105c81909e2a4e368aae36e8 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:33 p.m.