Triple

T23464280
Position Surface form Disambiguated ID Type / Status
Subject Lagrange Prize E569062 entity
Predicate location P40 FINISHED
Object Turin NE NERFINISHED

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: [Lagrange Prize, location, Turin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin
Context triple: [Lagrange Prize, location, 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 (2 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a69f0a54819084c19c248a572253 completed April 29, 2026, 6:35 a.m.
Created at: April 17, 2026, 5:54 p.m.