Triple

T734650
Position Surface form Disambiguated ID Type / Status
Subject Overijssel E14902 entity
Predicate containsCity P294 FINISHED
Object Kampen
Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
E87640 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: Kampen | Statement: [Overijssel, containsCity, Kampen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampen
Context triple: [Overijssel, containsCity, Kampen]
  • A. Strijen
    Strijen is a small town and former municipality located on the Hoeksche Waard island in the Dutch province of South Holland.
  • B. Rammenau
    Rammenau is a village in Saxony, Germany, best known as the birthplace of the influential German philosopher Johann Gottlieb Fichte.
  • C. Battle for Land
    Battle for Land was a Fascist Italy agricultural and land reclamation initiative aimed at increasing arable land and showcasing the regime’s economic and ideological strength.
  • D. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • E. Sitzkrieg
    Sitzkrieg is the term used to describe the early phase of World War II on the Western Front characterized by little active military operations despite the state of war.
  • 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: Kampen
Triple: [Overijssel, containsCity, Kampen]
Generated description
Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kampen
Target entity description: Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
  • A. Strijen
    Strijen is a small town and former municipality located on the Hoeksche Waard island in the Dutch province of South Holland.
  • B. Rammenau
    Rammenau is a village in Saxony, Germany, best known as the birthplace of the influential German philosopher Johann Gottlieb Fichte.
  • C. Battle for Land
    Battle for Land was a Fascist Italy agricultural and land reclamation initiative aimed at increasing arable land and showcasing the regime’s economic and ideological strength.
  • D. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • E. Sitzkrieg
    Sitzkrieg is the term used to describe the early phase of World War II on the Western Front characterized by little active military operations despite the state of war.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5d8c6148190a468f2d95f7ec91f completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a5f0de4819083457c86e5e93ba0 completed March 3, 2026, 2:41 a.m.
NEDg Description generation batch_69a64b03246081908c20445a7a401008 completed March 3, 2026, 2:44 a.m.
NED2 Entity disambiguation (via description) batch_69a64b4e9cec8190a3dcc378f853be0d completed March 3, 2026, 2:45 a.m.
Created at: March 1, 2026, 7:37 p.m.