Triple

T299369
Position Surface form Disambiguated ID Type / Status
Subject Château de Boncourt E6163 entity
Predicate locatedIn P40 FINISHED
Object Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
 E56934 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: Boncourt | Statement: [Château de Boncourt, locatedIn, Boncourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Boncourt
Context triple: [Château de Boncourt, locatedIn, Boncourt]
  • A. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • B. Laconnex
    Laconnex is a small rural municipality in western Switzerland, located in the canton of Geneva near the French border.
  • C. Chêne-Bourg
    Chêne-Bourg is a municipality in western Switzerland located in the canton of Geneva, forming part of the Geneva metropolitan area near the French border.
  • D. Modane
    Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
  • E. Limoges
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • 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: Boncourt
Triple: [Château de Boncourt, locatedIn, Boncourt]
Generated description
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Boncourt
Target entity description: Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
  • A. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • B. Laconnex
    Laconnex is a small rural municipality in western Switzerland, located in the canton of Geneva near the French border.
  • C. Chêne-Bourg
    Chêne-Bourg is a municipality in western Switzerland located in the canton of Geneva, forming part of the Geneva metropolitan area near the French border.
  • D. Modane
    Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
  • E. Limoges
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e9e53b2c81909c4a15b366d94cd6 completed Feb. 28, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44cb1bfe48190b8b7523b95d4a099 completed March 1, 2026, 2:26 p.m.
NEDg Description generation batch_69a44d42f6548190ba83a589c46be961 completed March 1, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_69a44d93a1d881908c1ac2685b7ffc6c completed March 1, 2026, 2:30 p.m.
Created at: Feb. 28, 2026, 1:06 p.m.