Triple

T15896724
Position Surface form Disambiguated ID Type / Status
Subject Villa Geno E385474 entity
Predicate proximityTo P350 FINISHED
Object Como city center
Como city center is the historic and commercial heart of the lakeside city of Como in northern Italy, known for its medieval streets, waterfront promenades, and proximity to Lake Como’s main attractions.
 E1182940 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: Como city center | Statement: [Villa Geno, proximityTo, Como city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Como city center
Context triple: [Villa Geno, proximityTo, Como city center]
  • A. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • B. City Center
    City Center is a historic performing arts venue in Midtown Manhattan, best known for its dance, theater, and music programming.
  • C. Centro
    Centro is a municipality in the Mexican state of Tabasco whose administrative center is the city of Villahermosa.
  • D. Centro
    Centro is the central urban district and main commercial hub of Novo Hamburgo in Rio Grande do Sul, Brazil.
  • E. Centro
    Centro is the historic downtown district of São Paulo, Brazil, known as the city’s main commercial, financial, and cultural hub.
  • 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: Como city center
Triple: [Villa Geno, proximityTo, Como city center]
Generated description
Como city center is the historic and commercial heart of the lakeside city of Como in northern Italy, known for its medieval streets, waterfront promenades, and proximity to Lake Como’s main attractions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Como city center
Target entity description: Como city center is the historic and commercial heart of the lakeside city of Como in northern Italy, known for its medieval streets, waterfront promenades, and proximity to Lake Como’s main attractions.
  • A. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • B. City Center
    City Center is a historic performing arts venue in Midtown Manhattan, best known for its dance, theater, and music programming.
  • C. Centro
    Centro is a municipality in the Mexican state of Tabasco whose administrative center is the city of Villahermosa.
  • D. Centro
    Centro is the central urban district and main commercial hub of Novo Hamburgo in Rio Grande do Sul, Brazil.
  • E. Centro
    Centro is the historic downtown district of São Paulo, Brazil, known as the city’s main commercial, financial, and cultural hub.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15639c9748190b1115f74cbd61330 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb04b55ec8190a5b3513b2afa4f83 completed May 9, 2026, 10:08 p.m.
NEDg Description generation batch_69ffb13fdb6c819091c3ee5c1f199031 completed May 9, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69ffb208aef881909b3a00e0015c27df completed May 9, 2026, 10:15 p.m.
Created at: April 10, 2026, 4:51 a.m.