Triple

T1861604
Position Surface form Disambiguated ID Type / Status
Subject Tuscany E34826 entity
Predicate containsCity P294 FINISHED
Object Arezzo E144823 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: Arezzo | Statement: [Tuscany, containsCity, Arezzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arezzo
Context triple: [Tuscany, containsCity, Arezzo]
  • A. Arezzo chosen
    Arezzo is an ancient Tuscan city in central Italy, historically significant as one of the principal centers of the Etruscan civilization and later a prominent medieval and Renaissance town.
  • B. Grosseto
    Grosseto is a Tuscan city near Italy’s western coast, known for its well-preserved medieval walls and role as the capital of the Maremma region.
  • C. Perugia
    Perugia is a historic hilltop city in central Italy, renowned for its Etruscan heritage, medieval architecture, and vibrant cultural and university life.
  • D. Gubbio
    Gubbio is a historic medieval town in the Umbria region of central Italy, known for its well-preserved stone architecture and traditional festivals.
  • E. Città di Castello
    Città di Castello is a historic town in the Umbria region of central Italy, known for its medieval architecture, Renaissance art, and location along the upper Tiber River.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb09e714881909cef0f7e77b5b3b9 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055827da881909a589a8d5c577eb9 completed March 10, 2026, 5:31 p.m.
Created at: March 4, 2026, 7:34 p.m.