Triple

T15016452
Position Surface form Disambiguated ID Type / Status
Subject Asturian mining basin E377970 entity
Predicate containsSettlement P847 FINISHED
Object Mieres E1069143 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: Mieres | Statement: [Asturian mining basin, containsSettlement, Mieres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mieres
Context triple: [Asturian mining basin, containsSettlement, Mieres]
  • A. Mieres chosen
    Mieres is a town in the Asturias region of northern Spain known for its industrial and mining heritage and as a local educational hub.
  • B. Segorbe
    Segorbe is a historic town in eastern Spain known for its medieval architecture and traditional festivals, located in the Valencian Community.
  • C. Brunete
    Brunete is a town in the Community of Madrid, Spain, historically notable as a major battleground of the Spanish Civil War.
  • D. Sarria
    Sarria is a historic town in the province of Lugo, Galicia, Spain, known today as a major starting point on the Camino de Santiago pilgrimage route.
  • E. La Bañeza
    La Bañeza is a small historic city in northwestern Spain known for its cultural festivals and traditional architecture.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7633fcc8190b2231f43252bc46f completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe96ae110c8190a0555590b9ddb36a completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:55 a.m.