Triple

T6686316
Position Surface form Disambiguated ID Type / Status
Subject Velletri E152105 entity
Predicate hasTwinTown P919 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: [Velletri, hasTwinTown, Orvieto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orvieto
Context triple: [Velletri, hasTwinTown, 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 municipality in the Caldas Department of Colombia, known for its coffee production and scenic Andean landscapes.
  • D. 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.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14cd6748190aad4badd5f253478 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eeb127248190bbee7a9f69c2b980 completed March 28, 2026, 3:07 p.m.
Created at: March 27, 2026, 2:04 p.m.