Triple

T14794854
Position Surface form Disambiguated ID Type / Status
Subject Caldas E347746 entity
Predicate hasMunicipality P847 FINISHED
Object Viterbo E263323 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: Viterbo | Statement: [Caldas, hasMunicipality, Viterbo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viterbo
Context triple: [Caldas, hasMunicipality, Viterbo]
  • A. 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.
  • B. Viterbo chosen
    Viterbo is a municipality in the Caldas Department of Colombia, known for its coffee production and scenic Andean landscapes.
  • C. 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.
  • D. Orvieto
    Orvieto is a historic hilltop city in Umbria, Italy, renowned for its dramatic cliffside setting and magnificent Gothic cathedral.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5fdd548190a2ee5e668c2b20b4 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce36ce08190930e791e2837d1a5 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 1:31 a.m.