Triple

T987561
Position Surface form Disambiguated ID Type / Status
Subject Flanders E21312 entity
Predicate contains P35 FINISHED
Object Hasselt
Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
 E165235 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: Hasselt | Statement: [Flanders, contains, Hasselt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hasselt
Context triple: [Flanders, contains, Hasselt]
  • A. Hasselt
    Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
  • B. Vilvoorde
    Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
  • C. Leuven
    Leuven is a historic Belgian city known for hosting KU Leuven, one of Europe’s leading research universities, and for its vibrant academic and cultural life.
  • D. Mechelen
    Mechelen is a historic city in the Flemish region of Belgium, known for its rich architectural heritage, medieval center, and prominent role in the Low Countries’ political and religious history.
  • E. Liège
    Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
  • 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: Hasselt
Triple: [Flanders, contains, Hasselt]
Generated description
Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hasselt
Target entity description: Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
  • A. Hasselt
    Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
  • B. Vilvoorde
    Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
  • C. Leuven
    Leuven is a historic Belgian city known for hosting KU Leuven, one of Europe’s leading research universities, and for its vibrant academic and cultural life.
  • D. Mechelen
    Mechelen is a historic city in the Flemish region of Belgium, known for its rich architectural heritage, medieval center, and prominent role in the Low Countries’ political and religious history.
  • E. Liège
    Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4a7754c8190a10ba0587bd8323d completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08995af88190930a952bd32cd918 completed March 8, 2026, 5:26 a.m.
NEDg Description generation batch_69ad098f9fd0819094d9478881ca1a46 completed March 8, 2026, 5:30 a.m.
NED2 Entity disambiguation (via description) batch_69ad0a6c7aa08190b21b00c03f04af27 completed March 8, 2026, 5:34 a.m.
Created at: March 1, 2026, 7:41 p.m.