Triple

T4710344
Position Surface form Disambiguated ID Type / Status
Subject Giulio Natta E104491 entity
Predicate workLocation P7 FINISHED
Object Pavia E109533 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: Pavia | Statement: [Giulio Natta, workLocation, Pavia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pavia
Context triple: [Giulio Natta, workLocation, Pavia]
  • A. Pavia
    Pavia is a municipality in the Philippine province of Iloilo known for its suburban character and proximity to Iloilo City.
  • B. Pavia chosen
    Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
  • C. Bobbio
    Bobbio is an Italian surname most notably borne by the influential 20th-century legal philosopher and political theorist Norberto Bobbio.
  • D. Vercelli
    Vercelli is a historic city in northern Italy’s Piedmont region, known for its medieval architecture and important role in rice cultivation.
  • E. Bergamo
    Bergamo is a historic city in northern Italy known for its medieval walled upper town, rich artistic heritage, and strategic location at the foothills of the Alps.
  • 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_69bd43eac3c08190af7e4020c6c3704c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63ee712c81908da60aa0df58efe0 completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be922a8fc08190ad2dd4ffc1697f08 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:17 p.m.