Triple

T14060409
Position Surface form Disambiguated ID Type / Status
Subject Verhagen E338328 entity
Predicate hasNotableBearer P458 FINISHED
Object Evert Verhagen
Evert Verhagen is a Dutch epidemiologist and researcher known for his work in sports injury prevention and public health.
E1094153 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: Evert Verhagen | Statement: [Verhagen, hasNotableBearer, Evert Verhagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evert Verhagen
Context triple: [Verhagen, hasNotableBearer, Evert Verhagen]
  • A. Sven Groeneveld
    Sven Groeneveld is a Dutch professional tennis coach known for working with numerous top-ranked players on the WTA and ATP tours.
  • B. Dennis van Aarssen
    Dennis van Aarssen is a Dutch jazz and pop singer who gained national fame after winning the talent show The Voice of Holland.
  • C. Roel van Velzen
    Roel van Velzen is a Dutch singer-songwriter, musician, and television personality best known as the frontman of the pop-rock band VanVelzen and as a coach on The Voice of Holland.
  • D. Gertjan Verbeek
    Gertjan Verbeek is a Dutch football manager known for his stints in the Eredivisie, particularly for his work developing teams with an attacking style of play.
  • E. Jan Kleyna
    Jan Kleyna is an astronomer known for discovering small outer moons of Jupiter and contributing to the study of planetary satellites.
  • 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: Evert Verhagen
Triple: [Verhagen, hasNotableBearer, Evert Verhagen]
Generated description
Evert Verhagen is a Dutch epidemiologist and researcher known for his work in sports injury prevention and public health.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Evert Verhagen
Target entity description: Evert Verhagen is a Dutch epidemiologist and researcher known for his work in sports injury prevention and public health.
  • A. Sven Groeneveld
    Sven Groeneveld is a Dutch professional tennis coach known for working with numerous top-ranked players on the WTA and ATP tours.
  • B. Dennis van Aarssen
    Dennis van Aarssen is a Dutch jazz and pop singer who gained national fame after winning the talent show The Voice of Holland.
  • C. Roel van Velzen
    Roel van Velzen is a Dutch singer-songwriter, musician, and television personality best known as the frontman of the pop-rock band VanVelzen and as a coach on The Voice of Holland.
  • D. Gertjan Verbeek
    Gertjan Verbeek is a Dutch football manager known for his stints in the Eredivisie, particularly for his work developing teams with an attacking style of play.
  • E. Jan Kleyna
    Jan Kleyna is an astronomer known for discovering small outer moons of Jupiter and contributing to the study of planetary satellites.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd466febb88190986eb8f033d29279 completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd47fa764c8190b1d691f5847b7a05 completed May 8, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69fd492226888190a014b23e506ab19c completed May 8, 2026, 2:23 a.m.
Created at: April 9, 2026, 10:21 p.m.