Triple

T4670818
Position Surface form Disambiguated ID Type / Status
Subject Franches-Montagnes E102956 entity
Predicate contains P35 FINISHED
Object Le Bémont
Le Bémont is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau and known for its rural, pastoral landscape.
 E460809 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 Bémont | Statement: [Franches-Montagnes, contains, Le Bémont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Le Bémont
Context triple: [Franches-Montagnes, contains, Le Bémont]
  • A. La Baille
    La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
  • B. Mansois
    Mansois is a local name for the red wine grape variety Fer Servadou, traditionally used in the wines of southwest France.
  • C. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • D. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • 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: Le Bémont
Triple: [Franches-Montagnes, contains, Le Bémont]
Generated description
Le Bémont is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau and known for its rural, pastoral landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Le Bémont
Target entity description: Le Bémont is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau and known for its rural, pastoral landscape.
  • A. La Baille
    La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
  • B. Mansois
    Mansois is a local name for the red wine grape variety Fer Servadou, traditionally used in the wines of southwest France.
  • C. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • D. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd634ef5608190925663e988e3585b completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0390c238819089fb54648dfe1e64 completed March 21, 2026, 2:33 a.m.
NEDg Description generation batch_69be0542daf08190b792855c8129ac50 completed March 21, 2026, 2:41 a.m.
NED2 Entity disambiguation (via description) batch_69be05c1dcd48190a08a5748e86a5ac8 completed March 21, 2026, 2:43 a.m.
Created at: March 20, 2026, 1:15 p.m.