Triple

T1135035
Position Surface form Disambiguated ID Type / Status
Subject North Brabant E23119 entity
Predicate containsCity P294 FINISHED
Object Roosendaal
Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
E522007 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: Roosendaal | Statement: [North Brabant, containsCity, Roosendaal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roosendaal
Context triple: [North Brabant, containsCity, Roosendaal]
  • A. Apeldoorn
    Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
  • B. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • C. Helmond
    Helmond is a city in the southern Netherlands known for its historic castle, industrial heritage, and location near Eindhoven in the province of North Brabant.
  • D. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • E. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • 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: Roosendaal
Triple: [North Brabant, containsCity, Roosendaal]
Generated description
Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Roosendaal
Target entity description: Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • A. Apeldoorn
    Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
  • B. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • C. Helmond
    Helmond is a city in the southern Netherlands known for its historic castle, industrial heritage, and location near Eindhoven in the province of North Brabant.
  • D. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • E. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bbfffaa48190b2534ff4da3544ce completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4865e65c81909165e7c6fed0d2ff completed March 22, 2026, 1:39 a.m.
NEDg Description generation batch_69bf492769b08190a3675893ff3473c1 completed March 22, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_69bf49956ee48190b74fa50728d4248b completed March 22, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:44 p.m.