Triple

T7699027
Position Surface form Disambiguated ID Type / Status
Subject Rosa Vercellana E174441 entity
Predicate residence P75 FINISHED
Object Turin E15144 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: Turin | Statement: [Rosa Vercellana, residence, Turin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin
Context triple: [Rosa Vercellana, residence, Turin]
  • A. Turin chosen
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • B. Turin
    Turin is a small town located in Coweta County in the U.S. state of Georgia.
  • C. Turin
    Turin is the codename for a generation of AMD EPYC server processors based on the Zen 5 architecture, targeting high-performance and data center workloads.
  • D. Metropolitan City of Turin
    The Metropolitan City of Turin is an Italian administrative region in Piedmont that encompasses the city of Turin and its surrounding municipalities, coordinating local governance, infrastructure, and regional development.
  • E. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • 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_69c6995a72cc8190998e56daa6f8e453 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7026a8268819097c03458ed263a55 completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b50049f88190b4cd5cf692d0a3b1 completed March 29, 2026, 5:13 a.m.
Created at: March 27, 2026, 4:03 p.m.