Triple

T555643
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Italy E11935 entity
Predicate majorCity P316 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: [Kingdom of Italy, majorCity, Turin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin
Context triple: [Kingdom of Italy, majorCity, 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. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • C. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • D. Parma
    Parma is a historic city in northern Italy renowned for its rich artistic heritage, architecture, and culinary traditions, including Parmigiano Reggiano cheese and Parma ham.
  • E. Bologna
    Bologna is a historic city in northern Italy renowned for its medieval architecture, rich culinary tradition, and the University of Bologna, one of the oldest universities in the world.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4991dd7008190a6c1bc8bc832456d completed March 1, 2026, 7:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf473e48819095390a5904429a9c completed March 4, 2026, 6:20 a.m.
Created at: March 1, 2026, 7:32 p.m.