Triple

T17013663
Position Surface form Disambiguated ID Type / Status
Subject Rheden E412761 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Spankeren
Spankeren is a small village in the Dutch province of Gelderland, located near the town of Rheden.
E1247027 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: Spankeren | Statement: [Rheden, hasNearbySettlement, Spankeren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spankeren
Context triple: [Rheden, hasNearbySettlement, Spankeren]
  • A. Krabbendijke
    Krabbendijke is a village in the Dutch province of Zeeland, known for its agricultural surroundings and location on the former island of Zuid-Beveland.
  • B. Spijkerboor
    Spijkerboor is a small village in the Dutch province of North Holland, situated within the municipality of Wormerland.
  • C. Spijkerboor
    Spijkerboor is a small village in the Dutch province of South Holland, known for its location amid the lakes and waterways of the Kagerplassen area.
  • D. De Baarsjes
    De Baarsjes is a residential neighborhood in Amsterdam, Netherlands, known for its diverse population, early 20th-century architecture, and canalside urban character.
  • E. Spijk
    Spijk is a small village in the Dutch province of Groningen, known for its rural character and historic setting near the Ems estuary.
  • 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: Spankeren
Triple: [Rheden, hasNearbySettlement, Spankeren]
Generated description
Spankeren is a small village in the Dutch province of Gelderland, located near the town of Rheden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Spankeren
Target entity description: Spankeren is a small village in the Dutch province of Gelderland, located near the town of Rheden.
  • A. Krabbendijke
    Krabbendijke is a village in the Dutch province of Zeeland, known for its agricultural surroundings and location on the former island of Zuid-Beveland.
  • B. Spijkerboor
    Spijkerboor is a small village in the Dutch province of North Holland, situated within the municipality of Wormerland.
  • C. Spijkerboor
    Spijkerboor is a small village in the Dutch province of South Holland, known for its location amid the lakes and waterways of the Kagerplassen area.
  • D. De Baarsjes
    De Baarsjes is a residential neighborhood in Amsterdam, Netherlands, known for its diverse population, early 20th-century architecture, and canalside urban character.
  • E. Spijk
    Spijk is a small village in the Dutch province of Groningen, known for its rural character and historic setting near the Ems estuary.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47dab688190bf486bcf0b40ed4f completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4990948190861ff81f8fc3e8f2 completed May 10, 2026, 11:56 p.m.
NEDg Description generation batch_6a011cc1afc48190b83e3203407c1d7f completed May 11, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a011d67c82c8190b737406e8952eb2b completed May 11, 2026, 12:05 a.m.
Created at: April 10, 2026, 5:33 a.m.