Triple

T7535003
Position Surface form Disambiguated ID Type / Status
Subject Southern Switzerland E178126 entity
Predicate hasMajorCity P316 FINISHED
Object Chiasso E263461 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: Chiasso | Statement: [Southern Switzerland, hasMajorCity, Chiasso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chiasso
Context triple: [Southern Switzerland, hasMajorCity, Chiasso]
  • A. Chiasso chosen
    Chiasso is a Swiss border town in the canton of Ticino, known as an important rail and road transit point between Switzerland and Italy.
  • B. Cernobbio
    Cernobbio is a picturesque town in northern Italy known for its lakeside villas and scenic location on the shores of Lake Como.
  • C. Lugano
    Lugano is a picturesque Swiss city in the Italian-speaking canton of Ticino, known for its lakeside setting on Lake Lugano, surrounding mountains, and role as a regional financial and cultural center.
  • D. Baveno
    Baveno is a picturesque lakeside town in northern Italy, known for its scenic views of Lake Maggiore and its historic villas and churches.
  • E. Ascona
    Ascona is a picturesque resort town on the shores of Lake Maggiore in the Swiss canton of Ticino, known for its mild climate, lakeside promenade, and vibrant cultural scene.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f84a9d28819084ebfc44fcb2c29c completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870741e2481909020633203003a68 completed March 29, 2026, 12:21 a.m.
Created at: March 27, 2026, 3:47 p.m.