Triple

T13959064
Position Surface form Disambiguated ID Type / Status
Subject Mendrisio E335743 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Genestrerio
Genestrerio is a village and former municipality in the canton of Ticino in southern Switzerland, now part of the municipality of Mendrisio near the Italian border.
 E1071408 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: Genestrerio | Statement: [Mendrisio, hasNeighboringMunicipality, Genestrerio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Genestrerio
Context triple: [Mendrisio, hasNeighboringMunicipality, Genestrerio]
  • A. Geneta
    Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
  • B. Genet
    Genet is the surname of Jean Genet, the influential 20th-century French novelist, playwright, and poet known for his provocative explorations of crime, marginalization, and identity.
  • C. Segeneiti
    Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
  • D. Geno
    Geno is a young male deer character from Disney's Bambi franchise, depicted as the son of Bambi and Faline.
  • E. Geno
    Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
  • 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: Genestrerio
Triple: [Mendrisio, hasNeighboringMunicipality, Genestrerio]
Generated description
Genestrerio is a village and former municipality in the canton of Ticino in southern Switzerland, now part of the municipality of Mendrisio near the Italian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Genestrerio
Target entity description: Genestrerio is a village and former municipality in the canton of Ticino in southern Switzerland, now part of the municipality of Mendrisio near the Italian border.
  • A. Geneta
    Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
  • B. Genet
    Genet is the surname of Jean Genet, the influential 20th-century French novelist, playwright, and poet known for his provocative explorations of crime, marginalization, and identity.
  • C. Segeneiti
    Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
  • D. Geno
    Geno is a young male deer character from Disney's Bambi franchise, depicted as the son of Bambi and Faline.
  • E. Geno
    Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7b2f908190aa32f22298964746 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1d490048190b28cb44dd4ec46c4 completed May 6, 2026, 8:17 p.m.
NEDg Description generation batch_69fba5646cb48190acd932f6fbd6fe62 completed May 6, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_69fba6525d0c8190a1ab15881030c11c completed May 6, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:17 p.m.