Triple

T15837084
Position Surface form Disambiguated ID Type / Status
Subject Batán metro station E384011 entity
Predicate symbolLocation P30881 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: [Batán metro station, symbolLocation, madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: madrid
Context triple: [Batán metro station, symbolLocation, 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. Madrid
    Madrid is a coastal municipality in the Philippine province of Surigao del Sur on the island of Mindanao.
  • D. 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.
  • E. Cantoblanco, Madrid
    Cantoblanco, Madrid is a northern district of Madrid known primarily as the site of the Autonomous University of Madrid’s main campus and associated research and residential facilities.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142e1fcd48190bcb884f6c65db847 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa93ddce4819086174b2549f5e12b completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:49 a.m.