Triple

T13048467
Position Surface form Disambiguated ID Type / Status
Subject Condroz E327385 entity
Predicate containsSettlement P847 FINISHED
Object Assesse
Assesse is a rural municipality and village in the Namur province of Wallonia, Belgium.
 E1018274 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: Assesse | Statement: [Condroz, containsSettlement, Assesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Assesse
Context triple: [Condroz, containsSettlement, Assesse]
  • A. Assu
    Assu is a municipality in the Brazilian state of Rio Grande do Norte, known for its regional commerce and cultural traditions in the semi-arid Northeast.
  • B. ASSE
    ASSE is the commonly used abbreviation for AS Saint-Étienne, a historic French professional football club known for its success in Ligue 1.
  • C. Ateste
    Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
  • D. Asprovalta
    Asprovalta is a coastal town in northern Greece known for its long sandy beaches and role as a popular summer tourist destination.
  • E. Asayish
    Asayish is the internal security and police force operating in the Kurdish-led Autonomous Administration of North and East Syria, responsible for maintaining public order and internal security in the region.
  • 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: Assesse
Triple: [Condroz, containsSettlement, Assesse]
Generated description
Assesse is a rural municipality and village in the Namur province of Wallonia, Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Assesse
Target entity description: Assesse is a rural municipality and village in the Namur province of Wallonia, Belgium.
  • A. Assu
    Assu is a municipality in the Brazilian state of Rio Grande do Norte, known for its regional commerce and cultural traditions in the semi-arid Northeast.
  • B. ASSE
    ASSE is the commonly used abbreviation for AS Saint-Étienne, a historic French professional football club known for its success in Ligue 1.
  • C. Ateste
    Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
  • D. Asprovalta
    Asprovalta is a coastal town in northern Greece known for its long sandy beaches and role as a popular summer tourist destination.
  • E. Asayish
    Asayish is the internal security and police force operating in the Kurdish-led Autonomous Administration of North and East Syria, responsible for maintaining public order and internal security in the region.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980b8811c81908577f092e2736610 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbd8f1308190992c0bd832e1b05e completed May 3, 2026, 4:15 a.m.
NEDg Description generation batch_69f6cd98d29c8190b33cb2cc6c477b1d completed May 3, 2026, 4:22 a.m.
NED2 Entity disambiguation (via description) batch_69f6ce23ca208190960409130c4c52a9 completed May 3, 2026, 4:25 a.m.
Created at: April 9, 2026, 8:57 p.m.