Triple

T21013959
Position Surface form Disambiguated ID Type / Status
Subject Spanish AVE E517620 entity
Predicate connectsCityPair P12329 FINISHED
Object Madrid–Málaga
Madrid–Málaga is a major Spanish high-speed rail route linking the nation’s capital with the coastal city of Málaga.
 E1465763 NE FINISHED

How this triple was built (4 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–Málaga | Statement: [Spanish AVE, connectsCityPair, Madrid–Málaga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Madrid–Málaga
Context triple: [Spanish AVE, connectsCityPair, Madrid–Málaga]
  • A. Madrid–Valencia
    Madrid–Valencia is a major high-speed rail corridor in Spain linking the capital Madrid with the Mediterranean coastal city of Valencia.
  • B. Madrid–Seville
    Madrid–Seville is a major high-speed rail corridor in Spain linking the nation’s capital with the capital of Andalusia.
  • 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. Madrid–Barcelona
    Madrid–Barcelona is a major high-speed rail corridor in Spain connecting the country’s capital with its leading Catalan metropolis.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Madrid–Málaga
Triple: [Spanish AVE, connectsCityPair, Madrid–Málaga]
Generated description
Madrid–Málaga is a major Spanish high-speed rail route linking the nation’s capital with the coastal city of Málaga.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Madrid–Málaga
Target entity description: Madrid–Málaga is a major Spanish high-speed rail route linking the nation’s capital with the coastal city of Málaga.
  • A. Madrid–Valencia
    Madrid–Valencia is a major high-speed rail corridor in Spain linking the capital Madrid with the Mediterranean coastal city of Valencia.
  • B. Madrid–Seville
    Madrid–Seville is a major high-speed rail corridor in Spain linking the nation’s capital with the capital of Andalusia.
  • 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. Madrid–Barcelona
    Madrid–Barcelona is a major high-speed rail corridor in Spain connecting the country’s capital with its leading Catalan metropolis.
  • F. None of above. chosen

Provenance (5 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc5764188190829de6f5abd6e00f completed April 21, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a095a48166481908f6f178b9ff539a6 completed May 17, 2026, 6:03 a.m.
NEDg Description generation batch_6a095b1cb97c8190b3ba95373bd21056 completed May 17, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_6a095bf3efa4819089368a3e80a41e15 completed May 17, 2026, 6:11 a.m.
Created at: April 16, 2026, 1:54 p.m.