Triple

T777784
Position Surface form Disambiguated ID Type / Status
Subject Swiss Plateau E16427 entity
Predicate contains P35 FINISHED
Object Delémont
Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
 E161079 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: Delémont | Statement: [Swiss Plateau, contains, Delémont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Delémont
Context triple: [Swiss Plateau, contains, Delémont]
  • A. Hermance
    Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern Switzerland.
  • B. Martigny
    Martigny is a historic town in southwestern Switzerland known as a cultural and transportation hub in the canton of Valais, near the Great St. Bernard Pass.
  • C. 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.
  • D. Bardonnex
    Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
  • E. Chêne-Bougeries
    Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
  • 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: Delémont
Triple: [Swiss Plateau, contains, Delémont]
Generated description
Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Delémont
Target entity description: Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
  • A. Hermance
    Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern Switzerland.
  • B. Martigny
    Martigny is a historic town in southwestern Switzerland known as a cultural and transportation hub in the canton of Valais, near the Great St. Bernard Pass.
  • C. 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.
  • D. Bardonnex
    Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
  • E. Chêne-Bougeries
    Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a74da7648190adfad56717d564df completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace5371c2c8190861a5cbf9d089e4f completed March 8, 2026, 2:55 a.m.
NEDg Description generation batch_69ace5db553c8190b0d09462411f3dcf completed March 8, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69ace647c04881908ab550505110c29b completed March 8, 2026, 3 a.m.
Created at: March 1, 2026, 7:37 p.m.