Triple

T1040187
Position Surface form Disambiguated ID Type / Status
Subject Piedmontese E22452 entity
Predicate spokenIn P2266 FINISHED
Object Vercelli
Vercelli is a historic city in northern Italy’s Piedmont region, known for its medieval architecture and important role in rice cultivation.
 E243615 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: Vercelli | Statement: [Piedmontese, spokenIn, Vercelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vercelli
Context triple: [Piedmontese, spokenIn, Vercelli]
  • A. Pavia
    Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
  • B. Biella
    Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
  • C. Alessandria
    Alessandria is a city in the Piedmont region of northwestern Italy, known as an important industrial and transportation hub.
  • D. 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.
  • E. Brescia
    Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic 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: Vercelli
Triple: [Piedmontese, spokenIn, Vercelli]
Generated description
Vercelli is a historic city in northern Italy’s Piedmont region, known for its medieval architecture and important role in rice cultivation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vercelli
Target entity description: Vercelli is a historic city in northern Italy’s Piedmont region, known for its medieval architecture and important role in rice cultivation.
  • A. Pavia
    Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
  • B. Biella
    Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
  • C. Alessandria
    Alessandria is a city in the Piedmont region of northwestern Italy, known as an important industrial and transportation hub.
  • D. 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.
  • E. Brescia
    Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82e4d2c81909ca1264852baf04d completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae650fa53c8190a6db9d10c97f9850 completed March 9, 2026, 6:13 a.m.
NEDg Description generation batch_69ae65bfafec8190adf80379cd5b34f3 completed March 9, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69ae6622b0688190bf90fa04780bbf80 completed March 9, 2026, 6:18 a.m.
Created at: March 1, 2026, 7:41 p.m.