Triple

T268645
Position Surface form Disambiguated ID Type / Status
Subject Lake Como E5575 entity
Predicate hasTownOnShore P969 FINISHED
Object Lecco
Lecco is an Italian town in the Lombardy region, known for its scenic location at the southeastern tip of Lake Como and its surrounding Alpine foothills.
 E35247 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: Lecco | Statement: [Lake Como, hasTownOnShore, Lecco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lecco
Context triple: [Lake Como, hasTownOnShore, Lecco]
  • A. Trento
    Trento is a historic city in northern Italy, known as the capital of Trentino and for its significant role in Catholic history and Alpine culture.
  • B. Padua
    Padua is a historic city in northern Italy renowned as a major cultural and academic center, home to one of Europe’s oldest universities.
  • C. Pescara
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • D. Bardonecchia
    Bardonecchia is an alpine town in northwestern Italy known as a ski resort and transport hub near the French border in the Susa Valley.
  • E. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and 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: Lecco
Triple: [Lake Como, hasTownOnShore, Lecco]
Generated description
Lecco is an Italian town in the Lombardy region, known for its scenic location at the southeastern tip of Lake Como and its surrounding Alpine foothills.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lecco
Target entity description: Lecco is an Italian town in the Lombardy region, known for its scenic location at the southeastern tip of Lake Como and its surrounding Alpine foothills.
  • A. Trento
    Trento is a historic city in northern Italy, known as the capital of Trentino and for its significant role in Catholic history and Alpine culture.
  • B. Padua
    Padua is a historic city in northern Italy renowned as a major cultural and academic center, home to one of Europe’s oldest universities.
  • C. Pescara
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • D. Bardonecchia
    Bardonecchia is an alpine town in northwestern Italy known as a ski resort and transport hub near the French border in the Susa Valley.
  • E. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and 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_69a25853594c8190b05ec3a586ec88bf completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a260cfb4cc81909771b2d496b84726 completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38f51aeac81908c6d398e650dc315 completed March 1, 2026, 12:58 a.m.
NEDg Description generation batch_69a38fbfac808190b2b551dcbfe6faff completed March 1, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69a3903779e88190a00c44a522e82022 completed March 1, 2026, 1:02 a.m.
Created at: Feb. 28, 2026, 2:57 a.m.