Triple

T15250613
Position Surface form Disambiguated ID Type / Status
Subject Trenord E364507 entity
Predicate serviceAreaIncludesCity P104835 FINISHED
Object Varese E214629 NE FINISHED

How this triple was built (2 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: Varese | Statement: [Trenord, serviceAreaIncludesCity, Varese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Varese
Context triple: [Trenord, serviceAreaIncludesCity, Varese]
  • A. Varese chosen
    Varese is a city in northern Italy known for its lakeside setting, surrounding Prealps, and role as an important economic and cultural center in the Lombardy region.
  • B. 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.
  • C. Busto Arsizio
    Busto Arsizio is an industrial city in the Lombardy region of northern Italy, known for its textile and manufacturing heritage and its location within the greater Milan metropolitan area.
  • D. Legnano
    Legnano is a town in the Lombardy region of northern Italy, historically known for its medieval Battle of Legnano and its industrial development.
  • 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f62b9c8190b9ad40e2d1912b63 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff3649d1408190a4fed26539de1849 completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:13 a.m.