Triple

T9349366
Position Surface form Disambiguated ID Type / Status
Subject Hofheim am Taunus E224974 entity
Predicate hasSubdivision P747 FINISHED
Object Diedenbergen
Diedenbergen is a district of the town Hofheim am Taunus in the German state of Hesse.
E792549 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: Diedenbergen | Statement: [Hofheim am Taunus, hasSubdivision, Diedenbergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diedenbergen
Context triple: [Hofheim am Taunus, hasSubdivision, Diedenbergen]
  • A. Beekdaelen
    Beekdaelen is a municipality in the Dutch province of Limburg, known for its rural landscape, historic villages, and rolling hills.
  • B. Nuweveldberge
    Nuweveldberge is a mountain range in South Africa that forms part of the Great Escarpment and is known for its rugged terrain and semi-arid Karoo landscapes.
  • C. Maasbracht
    Maasbracht is a town in the Dutch province of Limburg, known as an inland port and industrial center along the River Meuse.
  • D. Humbeek
    Humbeek is a village in the Flemish Brabant province of Belgium, known as one of the constituent towns of the municipality of Grimbergen.
  • E. Moortebeek
    Moortebeek is a residential district within the Brussels municipality of Anderlecht in Belgium.
  • 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: Diedenbergen
Triple: [Hofheim am Taunus, hasSubdivision, Diedenbergen]
Generated description
Diedenbergen is a district of the town Hofheim am Taunus in the German state of Hesse.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Diedenbergen
Target entity description: Diedenbergen is a district of the town Hofheim am Taunus in the German state of Hesse.
  • A. Beekdaelen
    Beekdaelen is a municipality in the Dutch province of Limburg, known for its rural landscape, historic villages, and rolling hills.
  • B. Nuweveldberge
    Nuweveldberge is a mountain range in South Africa that forms part of the Great Escarpment and is known for its rugged terrain and semi-arid Karoo landscapes.
  • C. Maasbracht
    Maasbracht is a town in the Dutch province of Limburg, known as an inland port and industrial center along the River Meuse.
  • D. Humbeek
    Humbeek is a village in the Flemish Brabant province of Belgium, known as one of the constituent towns of the municipality of Grimbergen.
  • E. Moortebeek
    Moortebeek is a residential district within the Brussels municipality of Anderlecht in Belgium.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f1198b88190adc0b01f7c1be36e completed April 1, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e43c31008190b542a9c5aa33f30e completed April 4, 2026, 10:13 a.m.
NEDg Description generation batch_69d0e587586c8190a73ce417f0b5adec completed April 4, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69d0e5eb2ce88190973acc2cc8ce254f completed April 4, 2026, 10:20 a.m.
Created at: March 30, 2026, 7:41 p.m.