Triple

T790640
Position Surface form Disambiguated ID Type / Status
Subject Jura E16904 entity
Predicate hasMunicipalities P747 FINISHED
Object Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
 E171059 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: Saignelégier | Statement: [Jura, hasMunicipalities, Saignelégier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saignelégier
Context triple: [Jura, hasMunicipalities, Saignelégier]
  • A. Chêne-Bougeries
    Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
  • B. Delémont
    Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
  • C. Bardonnex
    Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
  • D. Cluses
    Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
  • E. Montgenèvre
    Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
  • 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: Saignelégier
Triple: [Jura, hasMunicipalities, Saignelégier]
Generated description
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saignelégier
Target entity description: Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
  • A. Chêne-Bougeries
    Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
  • B. Delémont
    Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
  • C. Bardonnex
    Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
  • D. Cluses
    Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
  • E. Montgenèvre
    Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9e0f0081909d2a89387d6c08e1 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c88f89481908914e4f4c36cd009 completed March 8, 2026, 6:51 a.m.
NEDg Description generation batch_69ad1cfdd8788190b3c9f6e0d49ec350 completed March 8, 2026, 6:53 a.m.
NED2 Entity disambiguation (via description) batch_69ad1d75f4f8819090c397a4b2d3f839 completed March 8, 2026, 6:55 a.m.
Created at: March 1, 2026, 7:38 p.m.