Triple

T10660058
Position Surface form Disambiguated ID Type / Status
Subject Ulisse Dini E251198 entity
Predicate workLocation P7 FINISHED
Object Pisa E32982 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: Pisa | Statement: [Ulisse Dini, workLocation, Pisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa
Context triple: [Ulisse Dini, workLocation, Pisa]
  • A. Pisa chosen
    Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
  • B. Florence
    Florence is a city in northwestern Alabama known as part of the Muscle Shoals metropolitan area and for its rich musical and cultural heritage.
  • C. Florence
    Florence is a critically acclaimed interactive story and mobile video game that explores the emotional journey of a young woman's first love through minimalist gameplay and visual storytelling.
  • D. Florence
    Florence is a character in John Patrick's play "The Curious Savage," known as one of the eccentric residents of a sanatorium who helps explore themes of sanity, kindness, and societal values.
  • E. Florence
    Florence is a neighborhood in South Los Angeles known for its dense urban character, diverse working-class community, and proximity to major transportation corridors.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6e0174dc4819093e577993c65ed32 completed April 8, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69dbace2a5388190bb685d347dd8aa6c completed April 12, 2026, 2:32 p.m.
Created at: April 8, 2026, 9:07 p.m.