Triple

T9431307
Position Surface form Disambiguated ID Type / Status
Subject Novelas ejemplares E227380 entity
Predicate firstPublicationPlace P1364 FINISHED
Object Madrid E4617 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: Madrid | Statement: [Novelas ejemplares, firstPublicationPlace, Madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madrid
Context triple: [Novelas ejemplares, firstPublicationPlace, Madrid]
  • A. Madrid chosen
    Madrid is the capital and largest city of Spain, renowned for its rich cultural heritage, historic architecture, and vibrant arts and nightlife scenes.
  • B. Madrid
    Madrid is a municipality in the Cundinamarca department of Colombia, located near Bogotá and known for its floriculture and agricultural production.
  • C. Madri
    Madri is a princess from the Mahabharata epic, known as the second wife of King Pandu and the mother of the twins Nakula and Sahadeva.
  • D. Seville
    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.
  • E. Seville
    Seville is a small unincorporated rural community located in Volusia County, Florida, known for its agricultural surroundings and historic character.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e6059bc8190a7e98aef3caabd0b completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1104033c08190a3670b017bd984d5 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:49 p.m.