Triple

T22897657
Position Surface form Disambiguated ID Type / Status
Subject Bevaix E568218 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Fresens
Fresens is a small former municipality in the canton of Neuchâtel in western Switzerland.
 E1559602 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: Fresens | Statement: [Bevaix, neighboringMunicipality, Fresens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fresens
Context triple: [Bevaix, neighboringMunicipality, Fresens]
  • A. Frese
    Frese is the surname of American college basketball coach Brenda Frese, best known for leading the University of Maryland women's basketball program.
  • B. Fiser
    Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
  • C. Fuhse
    Fuhse is a river in Lower Saxony, Germany, that flows through several towns before joining the Aller River.
  • D. Ruland
    Ruland is a surname most notably associated with former professional basketball player and coach Jeff Ruland.
  • E. Maufe
    Maufe is a surname most notably associated with Sir Edward Maufe, a 20th-century British architect known for designing Guildford Cathedral and several prominent war memorials.
  • 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: Fresens
Triple: [Bevaix, neighboringMunicipality, Fresens]
Generated description
Fresens is a small former municipality in the canton of Neuchâtel in western Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fresens
Target entity description: Fresens is a small former municipality in the canton of Neuchâtel in western Switzerland.
  • A. Frese
    Frese is the surname of American college basketball coach Brenda Frese, best known for leading the University of Maryland women's basketball program.
  • B. Fiser
    Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
  • C. Fuhse
    Fuhse is a river in Lower Saxony, Germany, that flows through several towns before joining the Aller River.
  • D. Ruland
    Ruland is a surname most notably associated with former professional basketball player and coach Jeff Ruland.
  • E. Maufe
    Maufe is a surname most notably associated with Sir Edward Maufe, a 20th-century British architect known for designing Guildford Cathedral and several prominent war memorials.
  • 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_69e2458c23ec81908fa2570692c6614f completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1801358488190aa2a51f0943ea5bd completed April 29, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bb9c78b548190b65d3ca4f825b3db completed May 19, 2026, 1:15 a.m.
NEDg Description generation batch_6a0bba7a90a081908c3d42be43e5f1f9 completed May 19, 2026, 1:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0bbae04d1881909e652b74862b0644 completed May 19, 2026, 1:20 a.m.
Created at: April 17, 2026, 3:41 p.m.