Triple

T1460219
Position Surface form Disambiguated ID Type / Status
Subject New Left E31494 entity
Predicate hasMainRegion P285 FINISHED
Object Italy E863 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: Italy | Statement: [New Left, hasMainRegion, Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italy
Context triple: [New Left, hasMainRegion, Italy]
  • A. Italy chosen
    Italy is a Southern European country known for its influential history, art, cuisine, and role as a founding member of the European Union.
  • B. Italo
    Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
  • C. ITA
    ITA is a U.S. government agency within the Department of Commerce that promotes American exports, ensures fair trade, and supports U.S. businesses in the global marketplace.
  • D. 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.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c59d6dd88190b8ff3bda90aef7e2 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e71ffd481909dfd0f77201dc17c completed March 8, 2026, 5:51 a.m.
Created at: March 1, 2026, 8 p.m.