Triple

T11711011
Position Surface form Disambiguated ID Type / Status
Subject Carla Bruni E278372 entity
Predicate placeOfBirth P1 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: [Carla Bruni, placeOfBirth, Turin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin
Context triple: [Carla Bruni, placeOfBirth, 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a49f072c81909c6a964a92e5bc0c completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82a205f08190b1c0e856fdeece11 completed April 27, 2026, 3:37 p.m.
Created at: April 8, 2026, 9:40 p.m.