Triple

T1533647
Position Surface form Disambiguated ID Type / Status
Subject Creuse E32501 entity
Predicate subprefecture P9697 FINISHED
Object Aubusson
Aubusson is a town in central France renowned for its centuries-old tradition of tapestry and carpet weaving.
 E174869 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: Aubusson | Statement: [Creuse, subprefecture, Aubusson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aubusson
Context triple: [Creuse, subprefecture, Aubusson]
  • A. Limoges
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • B. Sèvres
    Sèvres is a commune in the southwestern suburbs of Paris, France, historically notable as the site where the post–World War I Treaty of Sèvres was concluded.
  • C. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • D. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • E. Gonesse
    Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
  • 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: Aubusson
Triple: [Creuse, subprefecture, Aubusson]
Generated description
Aubusson is a town in central France renowned for its centuries-old tradition of tapestry and carpet weaving.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aubusson
Target entity description: Aubusson is a town in central France renowned for its centuries-old tradition of tapestry and carpet weaving.
  • A. Limoges
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • B. Sèvres
    Sèvres is a commune in the southwestern suburbs of Paris, France, historically notable as the site where the post–World War I Treaty of Sèvres was concluded.
  • C. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • D. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • E. Gonesse
    Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f8df00819086f34847e2170e12 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad295a03d881909071fb437c2d19ba completed March 8, 2026, 7:46 a.m.
NEDg Description generation batch_69ad2a1957e481908b07d3f4df75fbfe completed March 8, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ad2b2929348190ac35ff8d405894d6 completed March 8, 2026, 7:54 a.m.
Created at: March 4, 2026, 7:26 p.m.