Triple

T1670399
Position Surface form Disambiguated ID Type / Status
Subject Saint Louis University E36110 entity
Predicate locatedIn P40 FINISHED
Object Madrid, Spain 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, Spain | Statement: [Saint Louis University, locatedIn, Madrid, Spain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madrid, Spain
Context triple: [Saint Louis University, locatedIn, Madrid, Spain]
  • 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. Seville, Spain
    Seville, Spain is a historic Andalusian city renowned for its Moorish-influenced architecture, vibrant flamenco culture, and landmarks such as the Seville Cathedral and the Alcázar.
  • D. Guadalajara, Spain
    Guadalajara, Spain is a historic city in central Spain’s Castilla-La Mancha region, known for its medieval architecture, including palaces, churches, and fortifications.
  • E. Martorell, Spain
    Martorell, Spain is a town in Catalonia best known as a major automotive manufacturing hub and home to SEAT’s main production plant.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa624285bc8190a763e99e548a3294 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6adefc088190b1c6173c4be1d5a2 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:29 p.m.