Triple

T4829136
Position Surface form Disambiguated ID Type / Status
Subject Monza E107899 entity
Predicate region P40 FINISHED
Object Brianza E19656 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: Brianza | Statement: [Monza, region, Brianza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brianza
Context triple: [Monza, region, Brianza]
  • A. Lombardy chosen
    Lombardy is a populous and economically powerful region in northern Italy, known for its capital Milan and its role as a major European hub for finance, fashion, and industry.
  • B. Triveneto
    Triveneto is a historical-geographical region in northeastern Italy that traditionally comprises Veneto, Trentino-Alto Adige/Südtirol, and Friuli Venezia Giulia.
  • C. Verbano-Cusio-Ossola
    Verbano-Cusio-Ossola is a province in Italy’s Piedmont region, known for its Alpine landscapes and lakes including Lake Maggiore and Lake Orta.
  • D. Brescian
    Brescian is a variety of the Lombard language traditionally spoken in and around the city of Brescia in northern Italy.
  • E. Monferrato
    Monferrato is a historic hilly wine-producing region in northwestern Italy, renowned for its vineyards, medieval towns, and cultural landscapes.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cc66c488190a49052e32411dc4b completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dd0bf7c8190a11065bb61def18e completed March 21, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:24 p.m.