Triple

T585300
Position Surface form Disambiguated ID Type / Status
Subject Turin E15144 entity
Predicate locatedIn P40 FINISHED
Object northern Italy E17724 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: northern Italy | Statement: [Turin, locatedIn, northern Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: northern Italy
Context triple: [Turin, locatedIn, northern Italy]
  • A. Northern Italy chosen
    Northern Italy is a geographically and economically significant region of Italy, known for its Alpine landscapes, industrial cities, and historical role as a major theater of European conflicts.
  • B. Lombardy
    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.
  • C. Emilia-Romagna
    Emilia-Romagna is a region in northern Italy known for its rich culinary traditions, historic cities, and strong industrial and agricultural economy.
  • D. Central Italy
    Central Italy is a geographical and cultural region of Italy known for its historic cities, rolling landscapes, and significant role in the country’s political and artistic heritage.
  • E. Veneto
    Veneto is a region in northeastern Italy known for its historic cities like Venice and Verona, rich cultural heritage, and diverse landscapes ranging from the Adriatic coast to the Dolomite mountains.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9874c88190bd1e08d4689ea124 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a523853a648190bdf48e8148fa642b completed March 2, 2026, 5:43 a.m.
Created at: March 1, 2026, 7:33 p.m.