Triple

T2709985
Position Surface form Disambiguated ID Type / Status
Subject Pertinax E59835 entity
Predicate birthPlace P1 FINISHED
Object Italia 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: Italia | Statement: [Pertinax, birthPlace, Italia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italia
Context triple: [Pertinax, birthPlace, Italia]
  • A. Włochy
    Włochy is a district in the southwestern part of Warsaw, Poland, known for its mix of residential areas, industrial zones, and major transport infrastructure including the city’s main airport.
  • B. 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.
  • C. Italian Republic
    The Italian Republic is a Southern European nation on the Apennine Peninsula, known for its rich cultural heritage, influential history in art and politics, and status as a founding member of the European Union.
  • D. Italo
    Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
  • E. Franca
    Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda7771a4819081904bd6b818b81b completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc030c9b88190934f96a8ff74c4a7 completed March 10, 2026, 6:54 a.m.
Created at: March 6, 2026, 9:55 p.m.