Triple

T20084992
Position Surface form Disambiguated ID Type / Status
Subject Giovanni Pisano E500101 entity
Predicate workLocation P7 FINISHED
Object Pistoia 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: Pistoia | Statement: [Giovanni Pisano, workLocation, Pistoia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pistoia
Context triple: [Giovanni Pisano, workLocation, Pistoia]
  • A. Pistoia chosen
    Pistoia is a historic Italian city known for its medieval architecture, vibrant cultural heritage, and location in the northern part of Tuscany.
  • B. Merate
    Merate is a town in the Lombardy region of northern Italy, known for its historic center and the Merate Astronomical Observatory.
  • 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. Lesignano
    Lesignano is a locality or subdivision within the municipality of Serravalle in San Marino.
  • 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.