Triple

T7091478
Position Surface form Disambiguated ID Type / Status
Subject Arrondissement of Caen E165203 entity
Predicate contains P35 FINISHED
Object Cheux
Cheux is a small commune in the Calvados department of the Normandy region in northwestern France.
 E640646 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: Cheux | Statement: [Arrondissement of Caen, contains, Cheux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cheux
Context triple: [Arrondissement of Caen, contains, Cheux]
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. Montmorency
    Montmorency is a Montreal Metro station in Laval that serves as the eastern terminus of the Orange Line and a key transit hub for the area.
  • C. Montmorency
    Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
  • D. Ozanne
    Ozanne is a river in France that serves as a right-bank tributary of the Loir.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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: Cheux
Triple: [Arrondissement of Caen, contains, Cheux]
Generated description
Cheux is a small commune in the Calvados department of the Normandy region in northwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cheux
Target entity description: Cheux is a small commune in the Calvados department of the Normandy region in northwestern France.
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. Montmorency
    Montmorency is a Montreal Metro station in Laval that serves as the eastern terminus of the Orange Line and a key transit hub for the area.
  • C. Montmorency
    Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
  • D. Ozanne
    Ozanne is a river in France that serves as a right-bank tributary of the Loir.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69c6887e8c10819091cee237560d32da completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e53132288190b6da361d9c7218ab completed March 27, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7948cb3d48190993134d709924e3d completed March 28, 2026, 8:42 a.m.
NEDg Description generation batch_69c7962ec0bc8190a9223ebb245d0914 completed March 28, 2026, 8:49 a.m.
NED2 Entity disambiguation (via description) batch_69c79709ed808190a9f09f5350ba2ffd completed March 28, 2026, 8:53 a.m.
Created at: March 27, 2026, 2:41 p.m.