Triple

T22731896
Position Surface form Disambiguated ID Type / Status
Subject Ari Behn E562154 entity
Predicate familyName P18 FINISHED
Object Behn
Behn is a surname most notably associated with Norwegian author and artist Ari Behn.
E1552235 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: Behn | Statement: [Ari Behn, familyName, Behn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Behn
Context triple: [Ari Behn, familyName, Behn]
  • A. Maud Angelica Behn
    Maud Angelica Behn is a Norwegian royal family member and the eldest daughter of Princess Märtha Louise of Norway and the late author Ari Behn.
  • B. Aphra Behn
    Aphra Behn was a pioneering 17th-century English playwright, poet, and novelist, often regarded as one of the first professional female writers in English literature.
  • C. Sosthenes Behn
    Sosthenes Behn was an American businessman and telecommunications pioneer best known for building a global phone empire and co-founding ITT Corporation.
  • D. Emma Tallulah Behn
    Emma Tallulah Behn is the youngest daughter of Norwegian Princess Märtha Louise and the late author Ari Behn, and a member of Norway’s extended royal family.
  • E. Margaret Wycherly
    Margaret Wycherly was an English-born American stage and film actress best known for her character roles in early 20th-century cinema, including her Oscar-nominated performance in "Sergeant York."
  • 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: Behn
Triple: [Ari Behn, familyName, Behn]
Generated description
Behn is a surname most notably associated with Norwegian author and artist Ari Behn.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Behn
Target entity description: Behn is a surname most notably associated with Norwegian author and artist Ari Behn.
  • A. Maud Angelica Behn
    Maud Angelica Behn is a Norwegian royal family member and the eldest daughter of Princess Märtha Louise of Norway and the late author Ari Behn.
  • B. Aphra Behn
    Aphra Behn was a pioneering 17th-century English playwright, poet, and novelist, often regarded as one of the first professional female writers in English literature.
  • C. Sosthenes Behn
    Sosthenes Behn was an American businessman and telecommunications pioneer best known for building a global phone empire and co-founding ITT Corporation.
  • D. Emma Tallulah Behn
    Emma Tallulah Behn is the youngest daughter of Norwegian Princess Märtha Louise and the late author Ari Behn, and a member of Norway’s extended royal family.
  • E. Margaret Wycherly
    Margaret Wycherly was an English-born American stage and film actress best known for her character roles in early 20th-century cinema, including her Oscar-nominated performance in "Sergeant York."
  • 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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1792de040819093aa904bf751a788 completed April 29, 2026, 3:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b8fca5f10819083604273aae3fcc3 completed May 18, 2026, 10:16 p.m.
NEDg Description generation batch_6a0b93bc59e481909e2fbee11a29b7a9 completed May 18, 2026, 10:33 p.m.
NED2 Entity disambiguation (via description) batch_6a0b9488db048190b73ff89215ffeb74 completed May 18, 2026, 10:36 p.m.
Created at: April 17, 2026, 3:21 p.m.