Triple

T4961269
Position Surface form Disambiguated ID Type / Status
Subject Anneke Wills E111412 entity
Predicate givenName P17 FINISHED
Object Anneke
Anneke is a feminine given name of Dutch origin, commonly used in the Netherlands and other Germanic-language regions.
E482260 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: Anneke | Statement: [Anneke Wills, givenName, Anneke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anneke
Context triple: [Anneke Wills, givenName, Anneke]
  • A. Anneke Harmensdr
    Anneke Harmensdr was the first wife of Dutch Golden Age portrait painter Frans Hals.
  • B. Saskia
    Saskia is a female given name of Germanic origin, most famously borne by Saskia van Uylenburgh, the wife and frequent model of the Dutch painter Rembrandt.
  • C. Annelies
    Annelies is the given first name of Anne Frank, the Jewish diarist whose writings from hiding during the Holocaust became world-famous.
  • D. Marijke
    Marijke is the baptismal name of Princess Christina of the Netherlands, the youngest daughter of Queen Juliana and Prince Bernhard.
  • E. Agneta
    Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
  • 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: Anneke
Triple: [Anneke Wills, givenName, Anneke]
Generated description
Anneke is a feminine given name of Dutch origin, commonly used in the Netherlands and other Germanic-language regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anneke
Target entity description: Anneke is a feminine given name of Dutch origin, commonly used in the Netherlands and other Germanic-language regions.
  • A. Anneke Harmensdr
    Anneke Harmensdr was the first wife of Dutch Golden Age portrait painter Frans Hals.
  • B. Saskia
    Saskia is a female given name of Germanic origin, most famously borne by Saskia van Uylenburgh, the wife and frequent model of the Dutch painter Rembrandt.
  • C. Annelies
    Annelies is the given first name of Anne Frank, the Jewish diarist whose writings from hiding during the Holocaust became world-famous.
  • D. Marijke
    Marijke is the baptismal name of Princess Christina of the Netherlands, the youngest daughter of Queen Juliana and Prince Bernhard.
  • E. Agneta
    Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
  • 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71dc06a48190827d54a5c0351aab completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81e7dba88190ab0f2d99a931cf0e completed March 21, 2026, 11:32 a.m.
NEDg Description generation batch_69be83006dac819093e3becdbc1c2925 completed March 21, 2026, 11:37 a.m.
NED2 Entity disambiguation (via description) batch_69be83614a508190b870e857436cbed2 completed March 21, 2026, 11:39 a.m.
Created at: March 20, 2026, 1:32 p.m.