Triple

T1900762
Position Surface form Disambiguated ID Type / Status
Subject Via Flaminia E37683 entity
Predicate passesThrough P225 FINISHED
Object Umbria E35541 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: Umbria | Statement: [Via Flaminia, passesThrough, Umbria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umbria
Context triple: [Via Flaminia, passesThrough, Umbria]
  • A. Umbria chosen
    Umbria is a central Italian region known for its historic hill towns, medieval architecture, and rich cultural heritage.
  • B. La Marche
    La Marche is a historic province in central France known for its rural landscapes and role as a frontier region between major medieval territories.
  • C. Abruzzo
    Abruzzo is a central Italian region known for its rugged Apennine mountains, national parks, and Adriatic Sea coastline.
  • D. Emilia-Romagna
    Emilia-Romagna is a region in northern Italy known for its rich culinary traditions, historic cities, and strong industrial and agricultural economy.
  • E. Tuscany
    Tuscany is a central Italian region renowned for its rolling landscapes, historic cities like Florence and Siena, and its pivotal role in art, culture, and the birth of the Renaissance.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb18c46c88190b10c05bf5c6a2d9c completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3042bdf08190bf43c9246fcc114e completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:35 p.m.