Triple

T8969844
Position Surface form Disambiguated ID Type / Status
Subject Norcia E214236 entity
Predicate historicalName P65 FINISHED
Object Nursia E153339 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: Nursia | Statement: [Norcia, historicalName, Nursia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nursia
Context triple: [Norcia, historicalName, Nursia]
  • A. Nursia chosen
    Nursia is an ancient town in central Italy, historically significant as the birthplace of Saint Benedict and known today as Norcia.
  • B. Raeti
    The Raeti were an ancient Alpine people of central Europe, known from Roman sources for inhabiting the mountainous regions that later formed the Roman province of Raetia.
  • C. Albia
    Albia is a small city in Monroe County, Iowa, serving as a local hub for the surrounding rural area in the south-central part of the state.
  • D. Carrù
    Carrù is a small town in Italy’s Piedmont region, known as the birthplace of former Italian President Luigi Einaudi and for its wine and truffle traditions.
  • E. Senigallia
    Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6765babc8190a4a3b79aa21047c8 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05be6550081908d42bbae3c00cae3 completed April 4, 2026, 12:31 a.m.
Created at: March 30, 2026, 7:02 p.m.