Triple

T2512612
Position Surface form Disambiguated ID Type / Status
Subject East Lansing E52734 entity
Predicate hasSisterCity P919 FINISHED
Object Collegno
Collegno is a municipality in the Metropolitan City of Turin in northern Italy, known as a residential and industrial suburb of Turin.
E312801 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: Collegno | Statement: [East Lansing, hasSisterCity, Collegno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collegno
Context triple: [East Lansing, hasSisterCity, Collegno]
  • A. Cuneo
    Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
  • B. Segrate
    Segrate is a municipality in the Metropolitan City of Milan in northern Italy, known for its proximity to Milan and its role as a residential and commercial suburb.
  • C. Grignano
    Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
  • D. Savigliano
    Savigliano is a historic town in the Piedmont region of northwestern Italy, known for its medieval architecture and role in the history of the House of Savoy.
  • E. Biella
    Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
  • 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: Collegno
Triple: [East Lansing, hasSisterCity, Collegno]
Generated description
Collegno is a municipality in the Metropolitan City of Turin in northern Italy, known as a residential and industrial suburb of Turin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Collegno
Target entity description: Collegno is a municipality in the Metropolitan City of Turin in northern Italy, known as a residential and industrial suburb of Turin.
  • A. Cuneo
    Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
  • B. Segrate
    Segrate is a municipality in the Metropolitan City of Milan in northern Italy, known for its proximity to Milan and its role as a residential and commercial suburb.
  • C. Grignano
    Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
  • D. Savigliano
    Savigliano is a historic town in the Piedmont region of northwestern Italy, known for its medieval architecture and role in the history of the House of Savoy.
  • E. Biella
    Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
  • 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_69ab4958e76481908a235377dd921c9e completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1efb5c48190a9b47b39a388412b completed March 7, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b08623c8188190b48615107b653b60 completed March 10, 2026, 8:59 p.m.
NEDg Description generation batch_69b0cf4aec348190bd23af013c5e90ba completed March 11, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69b0cfb38b788190a916b5c723bd804d completed March 11, 2026, 2:13 a.m.
Created at: March 6, 2026, 9:46 p.m.