Triple

T5658842
Position Surface form Disambiguated ID Type / Status
Subject Flemish Limburg E124685 entity
Predicate hasMunicipality P847 FINISHED
Object Riemst
Riemst is a municipality in the Belgian province of Limburg, known for its rural character and location near the borders with the Netherlands and Germany.
E549181 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: Riemst | Statement: [Flemish Limburg, hasMunicipality, Riemst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riemst
Context triple: [Flemish Limburg, hasMunicipality, Riemst]
  • A. Rastatt
    Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
  • B. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • C. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • 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: Riemst
Triple: [Flemish Limburg, hasMunicipality, Riemst]
Generated description
Riemst is a municipality in the Belgian province of Limburg, known for its rural character and location near the borders with the Netherlands and Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Riemst
Target entity description: Riemst is a municipality in the Belgian province of Limburg, known for its rural character and location near the borders with the Netherlands and Germany.
  • A. Rastatt
    Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
  • B. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • C. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • D. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • E. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of 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_69c0082774a481909d7e63fb2aad56ac completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022fd9b148190bd4aa9c43500949f completed March 22, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097d7e0fc81909f051f8789ef9fb9 completed March 23, 2026, 1:31 a.m.
NEDg Description generation batch_69c0989f7e58819098175e6eaacdb9ee completed March 23, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69c09cf3220481908c52b519e8495fff completed March 23, 2026, 1:52 a.m.
Created at: March 22, 2026, 3:42 p.m.