Triple

T13437813
Position Surface form Disambiguated ID Type / Status
Subject Wilhelmina Cooper E320275 entity
Predicate familyName P18 FINISHED
Object Behmenburg
Behmenburg is the birth surname of Dutch-born American supermodel and influential 1960s–70s modeling agency founder Wilhelmina Cooper.
E1040436 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: Behmenburg | Statement: [Wilhelmina Cooper, familyName, Behmenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Behmenburg
Context triple: [Wilhelmina Cooper, familyName, Behmenburg]
  • A. Behmen
    Behmen is the given name of Behmen von Bleibruck, a historical figure likely associated with German-speaking Central Europe.
  • B. Benkheim
    Benkheim is the former German name for the village now known as Banie Mazurskie in northeastern Poland.
  • C. Berd
    Berd is a small historic town in northeastern Armenia known for its medieval fortresses and scenic location in Tavush Province near the border with Azerbaijan.
  • D. Degahabur
    Degahabur is a town in eastern Ethiopia that serves as an administrative and commercial center within the Somali Region.
  • E. Manuchehr
    Manuchehr is a legendary king in Iranian mythology, celebrated in epic literature such as the Shahnameh as a just and heroic ruler of the early Pishdadian era.
  • 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: Behmenburg
Triple: [Wilhelmina Cooper, familyName, Behmenburg]
Generated description
Behmenburg is the birth surname of Dutch-born American supermodel and influential 1960s–70s modeling agency founder Wilhelmina Cooper.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Behmenburg
Target entity description: Behmenburg is the birth surname of Dutch-born American supermodel and influential 1960s–70s modeling agency founder Wilhelmina Cooper.
  • A. Behmen
    Behmen is the given name of Behmen von Bleibruck, a historical figure likely associated with German-speaking Central Europe.
  • B. Benkheim
    Benkheim is the former German name for the village now known as Banie Mazurskie in northeastern Poland.
  • C. Berd
    Berd is a small historic town in northeastern Armenia known for its medieval fortresses and scenic location in Tavush Province near the border with Azerbaijan.
  • D. Degahabur
    Degahabur is a town in eastern Ethiopia that serves as an administrative and commercial center within the Somali Region.
  • E. Manuchehr
    Manuchehr is a legendary king in Iranian mythology, celebrated in epic literature such as the Shahnameh as a just and heroic ruler of the early Pishdadian era.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee5ec488190bd0c1e990dbd2bc2 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7399215bc8190b846906b0f081e7f completed May 3, 2026, 12:03 p.m.
NEDg Description generation batch_69f73bd79b8c8190bf91865e22bd41d0 completed May 3, 2026, 12:13 p.m.
NED2 Entity disambiguation (via description) batch_69f73c45b0748190ab9b1b524d206c0d completed May 3, 2026, 12:15 p.m.
Created at: April 9, 2026, 9:40 p.m.