Triple

T2937324
Position Surface form Disambiguated ID Type / Status
Subject Northeastern Italy E79298 entity
Predicate contains P35 FINISHED
Object Verona E118557 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: Verona | Statement: [Northeastern Italy, contains, Verona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Verona
Context triple: [Northeastern Italy, contains, Verona]
  • A. Verona chosen
    Verona is a historic city in northern Italy renowned for its well-preserved Roman architecture and its association with Shakespeare’s "Romeo and Juliet."
  • B. Padua
    Padua is a historic city in northern Italy renowned as a major cultural and academic center, home to one of Europe’s oldest universities.
  • C. Brescia
    Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic hub.
  • D. Pavia
    Pavia is a municipality in the Philippine province of Iloilo known for its suburban character and proximity to Iloilo City.
  • E. Pavia
    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.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983f91c48190b409d8f522cab08b completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3ac3bc481909bf1d220fdf06488 completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 2:56 p.m.