Triple

T8225768
Position Surface form Disambiguated ID Type / Status
Subject Zaventem E192168 entity
Predicate hasSubdivision P747 FINISHED
Object Nossegem
Nossegem is a village in the Flemish Brabant province of Belgium, forming part of the municipality of Zaventem near Brussels.
E719631 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: Nossegem | Statement: [Zaventem, hasSubdivision, Nossegem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nossegem
Context triple: [Zaventem, hasSubdivision, Nossegem]
  • A. Edigheim
    Edigheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
  • B. Nattheim
    Nattheim is a municipality in the Heidenheim district of Baden-Württemberg in southern Germany.
  • C. Lothagam
    Lothagam is an archaeological and geological site in northern Kenya known for its ancient human burials and prominent rock formations along the western shore of Lake Turkana.
  • D. Radaur
    Radaur is a town in the Yamunanagar district of Haryana, India, known primarily as a local commercial and educational center for surrounding rural areas.
  • E. Mauregard
    Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
  • 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: Nossegem
Triple: [Zaventem, hasSubdivision, Nossegem]
Generated description
Nossegem is a village in the Flemish Brabant province of Belgium, forming part of the municipality of Zaventem near Brussels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nossegem
Target entity description: Nossegem is a village in the Flemish Brabant province of Belgium, forming part of the municipality of Zaventem near Brussels.
  • A. Edigheim
    Edigheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
  • B. Nattheim
    Nattheim is a municipality in the Heidenheim district of Baden-Württemberg in southern Germany.
  • C. Lothagam
    Lothagam is an archaeological and geological site in northern Kenya known for its ancient human burials and prominent rock formations along the western shore of Lake Turkana.
  • D. Radaur
    Radaur is a town in the Yamunanagar district of Haryana, India, known primarily as a local commercial and educational center for surrounding rural areas.
  • E. Mauregard
    Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
  • 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_69ca82c9a8ac81908b011c38698456e4 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb77fc10f48190b7e241c89885a478 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccee0fd9d0819094350c9c7887cabe completed April 1, 2026, 10:06 a.m.
NEDg Description generation batch_69ccf1bc720081908c4eabf58336318a completed April 1, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69cd05f26f9c8190a3cc00c03c6dda95 completed April 1, 2026, 11:48 a.m.
Created at: March 30, 2026, 5:45 p.m.