Triple

T8556905
Position Surface form Disambiguated ID Type / Status
Subject Gubbio E202591 entity
Predicate hasNearbyCity P350 FINISHED
Object Assisi E76823 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: Assisi | Statement: [Gubbio, hasNearbyCity, Assisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Assisi
Context triple: [Gubbio, hasNearbyCity, Assisi]
  • A. Assisi chosen
    Assisi is an Italian hill town in Umbria renowned as the birthplace of St. Francis and a major center of Christian pilgrimage.
  • B. Todi
    Todi is a historic hilltop town in central Italy known for its medieval architecture, scenic views over the Tiber Valley, and well-preserved city walls and churches.
  • 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. Perugia
    Perugia is a historic hilltop city in central Italy, renowned for its Etruscan heritage, medieval architecture, and vibrant cultural and university life.
  • E. Orvieto
    Orvieto is a historic hilltop city in Umbria, Italy, renowned for its dramatic cliffside setting and magnificent Gothic cathedral.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe946d1408190adc7dfb7b2173f9d completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea868de6881908e87270a1fea0e4b completed April 2, 2026, 5:33 p.m.
Created at: March 30, 2026, 6:20 p.m.