Triple

T5314609
Position Surface form Disambiguated ID Type / Status
Subject Maassluis E119115 entity
Predicate hasMayor P185 FINISHED
Object Gregor Rensen
Gregor Rensen is a Dutch politician who has served as the mayor of the city of Maassluis in the Netherlands.
E511809 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: Gregor Rensen | Statement: [Maassluis, hasMayor, Gregor Rensen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gregor Rensen
Context triple: [Maassluis, hasMayor, Gregor Rensen]
  • A. Saunder Jurriaans
    Saunder Jurriaans is an American composer and musician best known for his atmospheric film and television scores, often created in collaboration with Danny Bensi.
  • B. Rogier Stoffers
    Rogier Stoffers is a Dutch cinematographer known for his work on a range of international films and television productions.
  • C. Sebastian Tapijn
    Sebastian Tapijn was a military commander known for leading the defense of Maastricht during the Eighty Years' War.
  • D. Tim Kruithoff
    Tim Kruithoff is a German local politician who serves as the mayor of the city of Emden in Lower Saxony.
  • E. Leo Beenhakker
    Leo Beenhakker is a Dutch football manager renowned for coaching top clubs and national teams, including Real Madrid, Ajax, and the Netherlands.
  • 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: Gregor Rensen
Triple: [Maassluis, hasMayor, Gregor Rensen]
Generated description
Gregor Rensen is a Dutch politician who has served as the mayor of the city of Maassluis in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gregor Rensen
Target entity description: Gregor Rensen is a Dutch politician who has served as the mayor of the city of Maassluis in the Netherlands.
  • A. Saunder Jurriaans
    Saunder Jurriaans is an American composer and musician best known for his atmospheric film and television scores, often created in collaboration with Danny Bensi.
  • B. Rogier Stoffers
    Rogier Stoffers is a Dutch cinematographer known for his work on a range of international films and television productions.
  • C. Sebastian Tapijn
    Sebastian Tapijn was a military commander known for leading the defense of Maastricht during the Eighty Years' War.
  • D. Tim Kruithoff
    Tim Kruithoff is a German local politician who serves as the mayor of the city of Emden in Lower Saxony.
  • E. Leo Beenhakker
    Leo Beenhakker is a Dutch football manager renowned for coaching top clubs and national teams, including Real Madrid, Ajax, and the Netherlands.
  • 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd854d947081909e51b27e40940580 completed March 20, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf188d3a2c8190ad06d1b71ef73780 completed March 21, 2026, 10:15 p.m.
NEDg Description generation batch_69bf195d26e88190b86c16cd6adc7c5c completed March 21, 2026, 10:19 p.m.
NED2 Entity disambiguation (via description) batch_69bf1a0bbed08190bf21bd99343b90a4 completed March 21, 2026, 10:22 p.m.
Created at: March 20, 2026, 1:54 p.m.