Triple

T10083464
Position Surface form Disambiguated ID Type / Status
Subject Rixensart E213960 entity
Predicate contains P35 FINISHED
Object Rosières
Rosières is a village and district within the municipality of Rixensart in Walloon Brabant, Belgium.
E842885 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: Rosières | Statement: [Rixensart, contains, Rosières]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosières
Context triple: [Rixensart, contains, Rosières]
  • A. Lignères
    Lignères is a small commune in northern France located within the administrative area of the canton of Breteuil in the Eure department of Normandy.
  • B. Moreuil
    Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
  • C. Plombières
    Plombières is a municipality in the province of Liège in eastern Belgium, near the German and Dutch borders.
  • D. Chasseral
    Chasseral is a prominent mountain in the Jura range of western Switzerland, known for its panoramic views and telecommunications installations.
  • E. Lussy
    Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
  • 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: Rosières
Triple: [Rixensart, contains, Rosières]
Generated description
Rosières is a village and district within the municipality of Rixensart in Walloon Brabant, Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rosières
Target entity description: Rosières is a village and district within the municipality of Rixensart in Walloon Brabant, Belgium.
  • A. Lignères
    Lignères is a small commune in northern France located within the administrative area of the canton of Breteuil in the Eure department of Normandy.
  • B. Moreuil
    Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
  • C. Plombières
    Plombières is a municipality in the province of Liège in eastern Belgium, near the German and Dutch borders.
  • D. Chasseral
    Chasseral is a prominent mountain in the Jura range of western Switzerland, known for its panoramic views and telecommunications installations.
  • E. Lussy
    Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04352d081908f676444cd2d2578 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cbcc82988190903efb78d0a4ce81 completed April 5, 2026, 8:53 p.m.
NEDg Description generation batch_69d2cd242ed8819097895cb15cbb5d47 completed April 5, 2026, 8:59 p.m.
NED2 Entity disambiguation (via description) batch_69d2d1204f008190a9349c071c1e8d19 completed April 5, 2026, 9:16 p.m.
Created at: March 30, 2026, 9 p.m.