Triple

T1126064
Position Surface form Disambiguated ID Type / Status
Subject Guarino Guarini E24721 entity
Predicate workLocation P7 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: [Guarino Guarini, workLocation, Turin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin
Context triple: [Guarino Guarini, workLocation, 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. 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.
  • C. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • D. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • E. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdc2718819094f5519ffb56993b completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb7eeda88190bdedb28497fbd81e completed March 8, 2026, 10:43 p.m.
Created at: March 1, 2026, 7:44 p.m.