Triple

T5843356
Position Surface form Disambiguated ID Type / Status
Subject Geert Bourgeois E129646 entity
Predicate givenName P17 FINISHED
Object Geert
Geert is a masculine given name of Dutch origin commonly used in Belgium and the Netherlands.
 E549889 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: Geert | Statement: [Geert Bourgeois, givenName, Geert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Geert
Context triple: [Geert Bourgeois, givenName, Geert]
  • A. Goudriaan
    Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • B. Jeroen
    Jeroen is a common Dutch male given name, often associated internationally with figures such as politician Jeroen Dijsselbloem.
  • C. Frits
    Frits is a Dutch given name most notably borne by Frits Bolkestein, a prominent Dutch politician and former European Commissioner.
  • D. Adriaan
    Adriaan is a masculine given name of Dutch origin commonly used in the Netherlands and other Dutch-speaking regions.
  • E. Wouter
    Wouter is a Dutch historian of religion and leading scholar of Western esotericism.
  • 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: Geert
Triple: [Geert Bourgeois, givenName, Geert]
Generated description
Geert is a masculine given name of Dutch origin commonly used in Belgium and the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Geert
Target entity description: Geert is a masculine given name of Dutch origin commonly used in Belgium and the Netherlands.
  • A. Goudriaan
    Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • B. Jeroen
    Jeroen is a common Dutch male given name, often associated internationally with figures such as politician Jeroen Dijsselbloem.
  • C. Frits
    Frits is a Dutch given name most notably borne by Frits Bolkestein, a prominent Dutch politician and former European Commissioner.
  • D. Adriaan
    Adriaan is a masculine given name of Dutch origin commonly used in the Netherlands and other Dutch-speaking regions.
  • E. Wouter
    Wouter is a Dutch historian of religion and leading scholar of Western esotericism.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d9da0c8190970319d0dc2fc73f completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1a6587c8190b76b1005178c29a9 completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a2bd6cdc819096c6829dc8d5d61e completed March 23, 2026, 2:17 a.m.
NED2 Entity disambiguation (via description) batch_69c0a323d9248190aa803c27be3d5eec completed March 23, 2026, 2:19 a.m.
Created at: March 22, 2026, 3:54 p.m.