Triple

T10972218
Position Surface form Disambiguated ID Type / Status
Subject Famke Janssen E259268 entity
Predicate givenName P17 FINISHED
Object Famke
Famke is a feminine given name most widely recognized through Dutch actress and former fashion model Famke Janssen.
E897540 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: Famke | Statement: [Famke Janssen, givenName, Famke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Famke
Context triple: [Famke Janssen, givenName, Famke]
  • A. Femke
    Femke is a Dutch feminine given name, notably borne by politician Femke Halsema, the mayor of Amsterdam.
  • B. Anouk
    Anouk is a Dutch singer-songwriter known for her powerful rock vocals and numerous chart-topping hits in the Netherlands.
  • C. Carice
    Carice is a Dutch given name best known internationally through actress Carice van Houten.
  • D. Anna Feore
    Anna Feore is a Canadian volleyball player who has represented Canada’s women’s national team in international competition.
  • E. Marike
    Marike is a feminine given name of Dutch and Afrikaans origin, commonly used in the Netherlands and South Africa.
  • 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: Famke
Triple: [Famke Janssen, givenName, Famke]
Generated description
Famke is a feminine given name most widely recognized through Dutch actress and former fashion model Famke Janssen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Famke
Target entity description: Famke is a feminine given name most widely recognized through Dutch actress and former fashion model Famke Janssen.
  • A. Femke
    Femke is a Dutch feminine given name, notably borne by politician Femke Halsema, the mayor of Amsterdam.
  • B. Anouk
    Anouk is a Dutch singer-songwriter known for her powerful rock vocals and numerous chart-topping hits in the Netherlands.
  • C. Carice
    Carice is a Dutch given name best known internationally through actress Carice van Houten.
  • D. Anna Feore
    Anna Feore is a Canadian volleyball player who has represented Canada’s women’s national team in international competition.
  • E. Marike
    Marike is a feminine given name of Dutch and Afrikaans origin, commonly used in the Netherlands and South Africa.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7719b5edc81908c1019f81e78bd2e completed April 9, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7a0b3dc819084fbda3227caf5b5 completed April 18, 2026, 1 a.m.
NEDg Description generation batch_69e2ff1ffb8c8190ba97f3c2e3c8c601 completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e3261cc4f48190ba0e5645f37cd4b5 completed April 18, 2026, 6:35 a.m.
Created at: April 8, 2026, 9:24 p.m.