Triple

T11475643
Position Surface form Disambiguated ID Type / Status
Subject Don Giovanni E272018 entity
Predicate setting P1957 FINISHED
Object Seville E359506 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: Seville | Statement: [Don Giovanni, setting, Seville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seville
Context triple: [Don Giovanni, setting, Seville]
  • A. Seville chosen
    Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
  • B. Seville
    Seville is a small unincorporated rural community located in Volusia County, Florida, known for its agricultural surroundings and historic character.
  • C. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • D. Malaga
    Malaga is a white wine grape variety name historically used as a synonym for Sémillon in certain wine-growing regions.
  • E. Granada
    Granada is a small rural town in southeastern Colorado, historically known as the site of the World War II-era Amache Japanese American internment camp.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294c8dc48190a515f83c99405a3b completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69ef8201715c819090cbd7c1e3068bdd completed April 27, 2026, 3:34 p.m.
Created at: April 8, 2026, 9:36 p.m.