Triple

T2429060
Position Surface form Disambiguated ID Type / Status
Subject Catana E52799 entity
Predicate modernName P1213 FINISHED
Object Catania E82307 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: Catania | Statement: [Catana, modernName, Catania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catania
Context triple: [Catana, modernName, Catania]
  • A. Catania chosen
    Catania is a historic port city on the eastern coast of Sicily, Italy, known for its Baroque architecture and proximity to Mount Etna.
  • B. Palermo
    Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
  • C. Palermo
    Palermo is the historic capital of Sicily, renowned for its rich multicultural heritage, including a significant medieval Jewish presence, and its blend of Arab-Norman architecture, vibrant markets, and coastal setting.
  • D. Palermo
    Palermo is a municipality in the Huila Department of southern Colombia, known for its agricultural activities and proximity to the departmental capital, Neiva.
  • E. Messina
    Messina is a major port city in northeastern Sicily, Italy, located on the Strait of Messina opposite mainland Calabria.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc99e1b548190aca9a0ba72a9b0f7 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce7a1c908190919280545ae4443c completed March 10, 2026, 7:55 a.m.
Created at: March 6, 2026, 9:43 p.m.