Triple

T8091745
Position Surface form Disambiguated ID Type / Status
Subject Bernese Oberland E188881 entity
Predicate hasRiver P165 FINISHED
Object Simme
The Simme is a river in the Swiss canton of Bern that flows through the Bernese Oberland, known for its alpine scenery and contribution to the region’s hydropower and tourism.
 E710649 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: Simme | Statement: [Bernese Oberland, hasRiver, Simme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Simme
Context triple: [Bernese Oberland, hasRiver, Simme]
  • A. Simm
    Simm is an English surname most notably associated with actor John Simm, known for his roles in British television and film.
  • B. Simo
    Simo is a Finnish given name most famously borne by Simo Häyhä, a legendary World War II sniper.
  • C. Sitte
    Sitte is a German-language surname most notably associated with Austrian architect and urban theorist Camillo Sitte.
  • D. Seimone
    Seimone is a feminine given name most notably associated with WNBA star Seimone Augustus.
  • E. Susima
    Susima was an ancient Indian prince of the Maurya dynasty, known primarily as the elder son of Emperor Bindusara and rival claimant to the throne against his brother Ashoka.
  • 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: Simme
Triple: [Bernese Oberland, hasRiver, Simme]
Generated description
The Simme is a river in the Swiss canton of Bern that flows through the Bernese Oberland, known for its alpine scenery and contribution to the region’s hydropower and tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Simme
Target entity description: The Simme is a river in the Swiss canton of Bern that flows through the Bernese Oberland, known for its alpine scenery and contribution to the region’s hydropower and tourism.
  • A. Simm
    Simm is an English surname most notably associated with actor John Simm, known for his roles in British television and film.
  • B. Simo
    Simo is a Finnish given name most famously borne by Simo Häyhä, a legendary World War II sniper.
  • C. Sitte
    Sitte is a German-language surname most notably associated with Austrian architect and urban theorist Camillo Sitte.
  • D. Seimone
    Seimone is a feminine given name most notably associated with WNBA star Seimone Augustus.
  • E. Susima
    Susima was an ancient Indian prince of the Maurya dynasty, known primarily as the elder son of Emperor Bindusara and rival claimant to the throne against his brother Ashoka.
  • 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_69cc640dbab881908a8142ac472f3408 completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc651e3b4c81908408c9f08eca8e09 completed April 1, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69cc69531a3c8190b712b3df6beefb7b completed April 1, 2026, 12:39 a.m.
Created at: March 30, 2026, 5:30 p.m.