Triple

T20084993
Position Surface form Disambiguated ID Type / Status
Subject Giovanni Pisano E500101 entity
Predicate workLocation P7 FINISHED
Object Prato 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: Prato | Statement: [Giovanni Pisano, workLocation, Prato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prato
Context triple: [Giovanni Pisano, workLocation, Prato]
  • A. Prato chosen
    Prato is a historic Tuscan city in central Italy known for its textile industry, medieval architecture, and cultural heritage.
  • B. Scandicci
    Scandicci is a town in central Italy located just southwest of Florence, known as a residential and industrial area within the Tuscan metropolitan region.
  • C. 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.
  • D. Parma
    Parma is a suburban city located just southwest of Cleveland in northeastern Ohio, known as one of the largest cities in Cuyahoga County.
  • 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 (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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655ae9ec8190bde2f17452639de8 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.