Triple

T10871409
Position Surface form Disambiguated ID Type / Status
Subject Forte Lorenese E256661 entity
Predicate locatedOn P40 FINISHED
Object Italian Riviera di Versilia E123041 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: Italian Riviera di Versilia | Statement: [Forte Lorenese, locatedOn, Italian Riviera di Versilia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italian Riviera di Versilia
Context triple: [Forte Lorenese, locatedOn, Italian Riviera di Versilia]
  • A. Pisan coast
    The Pisan coast is a stretch of shoreline in Tuscany, Italy, known for its sandy beaches, seaside resorts, and Mediterranean landscapes along the Tyrrhenian Sea.
  • B. Rosignano Marittimo
    Rosignano Marittimo is a coastal town and comune in Tuscany, central Italy, known for its seaside resorts and proximity to the Tyrrhenian Sea.
  • C. Cannero Riviera
    Cannero Riviera is a picturesque lakeside town on the western shore of Lake Maggiore in northern Italy, known for its mild climate, historic castles, and scenic waterfront.
  • D. Viareggio chosen
    Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
  • E. Orbetello
    Orbetello is a coastal town and lagoon in Tuscany, central Italy, known historically as a seaplane base and military aviation 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75186e75c8190bf046ea666faff54 completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7dbea28819083511b56bcd7d4ce completed April 15, 2026, 8:41 p.m.
Created at: April 8, 2026, 9:21 p.m.