Triple

T4590905
Position Surface form Disambiguated ID Type / Status
Subject Viterbo E103483 entity
Predicate demonym P191 FINISHED
Object Viterbese E103483 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: Viterbese | Statement: [Viterbo, demonym, Viterbese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viterbese
Context triple: [Viterbo, demonym, Viterbese]
  • A. Frosinone
    Frosinone is a city in central Italy that serves as the capital of the province of the same name within the Lazio region.
  • B. Viterbo chosen
    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.
  • C. Viterbo
    Viterbo is a municipality in the Caldas Department of Colombia, known for its coffee production and scenic Andean landscapes.
  • D. Minturno
    Minturno is a historic town in the Lazio region of central Italy, known for its ancient Roman ruins and scenic position near the Tyrrhenian coast.
  • E. Pisae
    Pisae is the ancient Roman name for the city of Pisa in Tuscany, Italy, historically significant as a coastal settlement and later a prominent maritime republic.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5923c0c88190952137d448d474cf completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0cdc7e8819088758c1d6d8e866d completed March 21, 2026, 12:05 a.m.
Created at: March 20, 2026, 1:11 p.m.