Triple

T16898631
Position Surface form Disambiguated ID Type / Status
Subject Madrid public transport network E424375 entity
Predicate includesOperator P28828 FINISHED
Object EMT Madrid E587312 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: EMT Madrid | Statement: [Madrid public transport network, includesOperator, EMT Madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EMT Madrid
Context triple: [Madrid public transport network, includesOperator, EMT Madrid]
  • A. EMT Madrid chosen
    EMT Madrid is the public bus and urban transport company serving the city of Madrid, Spain.
  • B. EMT Valencia
    EMT Valencia is the main public bus operator providing urban transport services throughout the city of Valencia, Spain.
  • C. Humanes de Madrid
    Humanes de Madrid is a municipality in the Community of Madrid, Spain, located in the metropolitan area southwest of the capital.
  • D. BME Madrid
    BME Madrid is Spain’s main stock exchange, operated by Bolsas y Mercados Españoles and based in Madrid.
  • E. Valmadrid
    Valmadrid is a small municipality in the province of Zaragoza, Aragon, Spain, situated within the semi-arid landscapes characteristic of the Campo de Belchite region.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8da7b0481909111358871875023 completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7b0783c81909c87de503d5e7e3c completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.