Triple

T3135540
Position Surface form Disambiguated ID Type / Status
Subject Anna van Egmond E65518 entity
Predicate residence P75 FINISHED
Object Buren
Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
 E328878 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: Buren | Statement: [Anna van Egmond, residence, Buren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buren
Context triple: [Anna van Egmond, residence, Buren]
  • A. Montesson
    Montesson is a suburban commune in the Yvelines department of north-central France, located to the northwest of Paris along the Seine River.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Bertogne
    Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
  • D. Breyten
    Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
  • E. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • 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: Buren
Triple: [Anna van Egmond, residence, Buren]
Generated description
Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Buren
Target entity description: Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
  • A. Montesson
    Montesson is a suburban commune in the Yvelines department of north-central France, located to the northwest of Paris along the Seine River.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Bertogne
    Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
  • D. Breyten
    Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
  • E. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5637de0819089393429c4017298 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f8793488190aa31040edaf1d627 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2103d83688190b107ecbacac604c1 completed March 12, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b210a290088190aaa10a015519e1de completed March 12, 2026, 1:02 a.m.
Created at: March 8, 2026, 3:05 p.m.