Triple

T8092673
Position Surface form Disambiguated ID Type / Status
Subject Bléone River E188905 entity
Predicate flowsThrough P225 FINISHED
Object Le Brusquet
Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
 E711784 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: Le Brusquet | Statement: [Bléone River, flowsThrough, Le Brusquet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Le Brusquet
Context triple: [Bléone River, flowsThrough, Le Brusquet]
  • A. Le Roeulx
    Le Roeulx is a historic town in the province of Hainaut in Wallonia, Belgium, known for its castle, traditional architecture, and proximity to the Canal du Centre.
  • B. Les Breuleux
    Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
  • C. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • D. Larroquette
    Larroquette is the surname of John Larroquette, an American actor best known for his Emmy-winning role as Dan Fielding on the sitcom "Night Court."
  • E. La Baille
    La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
  • 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: Le Brusquet
Triple: [Bléone River, flowsThrough, Le Brusquet]
Generated description
Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Le Brusquet
Target entity description: Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
  • A. Le Roeulx
    Le Roeulx is a historic town in the province of Hainaut in Wallonia, Belgium, known for its castle, traditional architecture, and proximity to the Canal du Centre.
  • B. Les Breuleux
    Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
  • C. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • D. Larroquette
    Larroquette is the surname of John Larroquette, an American actor best known for his Emmy-winning role as Dan Fielding on the sitcom "Night Court."
  • E. La Baille
    La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42217a1881909792b08a2f06fb75 completed March 31, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc64112138819096050975d707d8ee completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc68647cec81909736383fbe73d2e8 completed April 1, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69cc69b93bbc8190be2338182dd57b17 completed April 1, 2026, 12:41 a.m.
Created at: March 30, 2026, 5:30 p.m.