Triple

T23006097
Position Surface form Disambiguated ID Type / Status
Subject municipality of Moerdijk E572772 entity
Predicate contains P35 FINISHED
Object Willemstad
Willemstad is a historic fortified town in the Dutch province of North Brabant, known for its star-shaped ramparts and well-preserved harbor.
 E1565002 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: Willemstad | Statement: [municipality of Moerdijk, contains, Willemstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Willemstad
Context triple: [municipality of Moerdijk, contains, Willemstad]
  • A. Willemstad
    Willemstad is the colorful, Dutch colonial-style port city that serves as the capital and cultural center of the Caribbean island of Curaçao.
  • B. Kralendijk
    Kralendijk is the main town and administrative center of the island of Bonaire in the Caribbean.
  • C. Oranjestad
    Oranjestad is the largest city and main commercial and tourism hub of Aruba, located on the island’s western coast.
  • D. Oranjestad
    Oranjestad is the main town and administrative center of the Caribbean island of Sint Eustatius, known for its historic colonial architecture and coastal setting.
  • E. Zaandam
    Zaandam is a city in the North Holland province of the Netherlands, known for its historic windmills, traditional wooden houses, and proximity to Amsterdam.
  • 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: Willemstad
Triple: [municipality of Moerdijk, contains, Willemstad]
Generated description
Willemstad is a historic fortified town in the Dutch province of North Brabant, known for its star-shaped ramparts and well-preserved harbor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Willemstad
Target entity description: Willemstad is a historic fortified town in the Dutch province of North Brabant, known for its star-shaped ramparts and well-preserved harbor.
  • A. Willemstad
    Willemstad is the colorful, Dutch colonial-style port city that serves as the capital and cultural center of the Caribbean island of Curaçao.
  • B. Kralendijk
    Kralendijk is the main town and administrative center of the island of Bonaire in the Caribbean.
  • C. Oranjestad
    Oranjestad is the largest city and main commercial and tourism hub of Aruba, located on the island’s western coast.
  • D. Oranjestad
    Oranjestad is the main town and administrative center of the Caribbean island of Sint Eustatius, known for its historic colonial architecture and coastal setting.
  • E. Zaandam
    Zaandam is a city in the North Holland province of the Netherlands, known for its historic windmills, traditional wooden houses, and proximity to Amsterdam.
  • 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_69e245b6a3ac81908087599eefe3e365 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1835706dc8190b3f9743c0f336bb2 completed April 29, 2026, 4:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bd3846500819094a1bb01797d22a5 completed May 19, 2026, 3:05 a.m.
NEDg Description generation batch_6a0bd41c89708190a3df2a798ca25c99 completed May 19, 2026, 3:08 a.m.
NED2 Entity disambiguation (via description) batch_6a0bd5263734819082ce8b1c3082243f completed May 19, 2026, 3:12 a.m.
Created at: April 17, 2026, 3:51 p.m.