Triple

T5145605
Position Surface form Disambiguated ID Type / Status
Subject University of Perugia E116061 entity
Predicate hasAdditionalCampus P116 FINISHED
Object Orvieto E196077 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: Orvieto | Statement: [University of Perugia, hasAdditionalCampus, Orvieto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orvieto
Context triple: [University of Perugia, hasAdditionalCampus, Orvieto]
  • A. Orvieto chosen
    Orvieto is a historic hilltop city in Umbria, Italy, renowned for its dramatic cliffside setting and magnificent Gothic cathedral.
  • B. Città della Pieve
    Città della Pieve is a historic hilltop town in Umbria, central Italy, known for its medieval architecture and artworks by the Renaissance painter Perugino.
  • C. Viterbo
    Viterbo is a historic city in central Italy known for its well-preserved medieval center, ancient thermal baths, and role as a papal residence in the 13th century.
  • D. Viterbo
    Viterbo is a municipality in the Caldas Department of Colombia, known for its coffee production and scenic Andean landscapes.
  • E. Montefiascone
    Montefiascone is a historic hilltop town in Italy’s Lazio region, known for its scenic views over Lake Bolsena and its production of the Est! Est!! Est!!! white wine.
  • 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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd78ac677881909ce8632f1a8af880 completed March 20, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe323ed188190ad52dec581218e07 completed March 22, 2026, 12:40 p.m.
Created at: March 20, 2026, 1:43 p.m.