Triple

T14756357
Position Surface form Disambiguated ID Type / Status
Subject Valencia, Carabobo, Venezuela E346738 entity
Predicate hasTransport P1298 FINISHED
Object Valencia Metro E764725 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: Valencia Metro | Statement: [Valencia, Carabobo, Venezuela, hasTransport, Valencia Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia Metro
Context triple: [Valencia, Carabobo, Venezuela, hasTransport, Valencia Metro]
  • A. Valencia Metro chosen
    Valencia Metro is the rapid transit system serving the city of Valencia in Venezuela, providing urban rail transportation across key areas of the metropolitan region.
  • B. Valencia Metro
    Valencia Metro is the rapid transit system serving the city of Valencia and its metropolitan area in Spain.
  • C. Seville Metro
    Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
  • D. Valencia tram network
    The Valencia tram network is a light rail system serving the city of Valencia and its coastal districts, providing urban and suburban public transport connections including access to the Poblats Marítims area.
  • E. Madrid Metro
    Madrid Metro is the extensive rapid transit system serving Spain’s capital, known for its large network, frequent service, and role as a primary mode of urban transportation.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7ef0fd48190bd4a8af128ef274c completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cea5d348190a84970da131292ee completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:30 a.m.