Triple

T16133930
Position Surface form Disambiguated ID Type / Status
Subject David di Donatello for Best Actress E391471 entity
Predicate locationCountry P308 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: [David di Donatello for Best Actress, locationCountry, Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italy
Context triple: [David di Donatello for Best Actress, locationCountry, 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. Italy
    Italy is a small rural town in Yates County, New York, known for its agricultural landscape and location in the Finger Lakes region.
  • C. Italia
    Italia is a feminine given name, often inspired by the country of Italy and used in various cultures.
  • D. 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.
  • E. Como, Italy
    Como, Italy is a picturesque city in northern Italy’s Lombardy region, renowned for its historic architecture and its location at the southern tip of Lake Como.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a039f0c8190a679e16a27f2dbe3 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a0ed9c8190a10fa88ee94811cb completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.