Triple

T2404227
Position Surface form Disambiguated ID Type / Status
Subject Het Hogeland E50238 entity
Predicate formedByMergerOf P77 FINISHED
Object De Marne
De Marne was a former municipality in the province of Groningen in the Netherlands, known for its rural landscape and coastal location along the Wadden Sea.
 E267264 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: De Marne | Statement: [Het Hogeland, formedByMergerOf, De Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: De Marne
Context triple: [Het Hogeland, formedByMergerOf, De Marne]
  • A. Sauldre
    Sauldre is a river in central France that flows through the Cher department and is a tributary of the larger Sauldre river system.
  • B. Sainte-Mesme
    Sainte-Mesme is a small commune in the Île-de-France region of north-central France.
  • C. Oise
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near Paris.
  • D. Pontgouin
    Pontgouin is a small commune in northern France’s Eure-et-Loir department, known for its rural setting and the Eure River running through it.
  • E. Ver-sur-Mer
    Ver-sur-Mer is a coastal village in Normandy, France, known for its location on Gold Beach, one of the key Allied landing sectors during the D-Day invasion of World War II.
  • 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: De Marne
Triple: [Het Hogeland, formedByMergerOf, De Marne]
Generated description
De Marne was a former municipality in the province of Groningen in the Netherlands, known for its rural landscape and coastal location along the Wadden Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: De Marne
Target entity description: De Marne was a former municipality in the province of Groningen in the Netherlands, known for its rural landscape and coastal location along the Wadden Sea.
  • A. Sauldre
    Sauldre is a river in central France that flows through the Cher department and is a tributary of the larger Sauldre river system.
  • B. Sainte-Mesme
    Sainte-Mesme is a small commune in the Île-de-France region of north-central France.
  • C. Oise
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near Paris.
  • D. Pontgouin
    Pontgouin is a small commune in northern France’s Eure-et-Loir department, known for its rural setting and the Eure River running through it.
  • E. Ver-sur-Mer
    Ver-sur-Mer is a coastal village in Normandy, France, known for its location on Gold Beach, one of the key Allied landing sectors during the D-Day invasion of World War II.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fa151081909bc6be528b29b315 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef09b92048190acfa3a85417f259c completed March 9, 2026, 4:08 p.m.
NEDg Description generation batch_69aef521b5048190aac3507ad20c6eee completed March 9, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_69aef6450a1c8190ad5a844b31bff220 completed March 9, 2026, 4:33 p.m.
Created at: March 4, 2026, 7:58 p.m.