Triple

T21816745
Position Surface form Disambiguated ID Type / Status
Subject Atocha E538622 entity
Predicate connectsToCity P4245 FINISHED
Object Málaga NE NERFINISHED

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: Málaga | Statement: [Atocha, connectsToCity, Málaga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Málaga
Context triple: [Atocha, connectsToCity, Málaga]
  • A. Málaga chosen
    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.
  • B. Malaga
    Malaga is a white wine grape variety name historically used as a synonym for Sémillon in certain wine-growing regions.
  • C. 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.
  • D. Seville
    Seville is a small unincorporated rural community located in Volusia County, Florida, known for its agricultural surroundings and historic character.
  • E. Maracena
    Maracena is a municipality in the province of Granada, in the autonomous community of Andalusia in southern Spain.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475038c8190abb9b1a20eb8ff50 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f07ccac9f08190b835ee7a40ecf4c2 completed April 28, 2026, 9:24 a.m.
Created at: April 16, 2026, 6:54 p.m.