Triple

T13314488
Position Surface form Disambiguated ID Type / Status
Subject Lleida Pirineus railway station E317154 entity
Predicate connectsTo P845 FINISHED
Object Málaga E35967 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: Málaga | Statement: [Lleida Pirineus railway station, connectsTo, Málaga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Málaga
Context triple: [Lleida Pirineus railway station, connectsTo, 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. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f8a86481909ea2942c63037b77 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f73061e90c81909badb0cd12b304a2 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:29 p.m.