Triple

T15570394
Position Surface form Disambiguated ID Type / Status
Subject Beiras E374222 entity
Predicate hasSubregion P285 FINISHED
Object Beira Interior E415565 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: Beira Interior | Statement: [Beiras, hasSubregion, Beira Interior]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beira Interior
Context triple: [Beiras, hasSubregion, Beira Interior]
  • A. Beira Interior chosen
    Beira Interior is a historical region in central Portugal known for its mountainous landscapes, fortified towns, and long-standing cultural and agricultural traditions.
  • B. Beira Baixa
    Beira Baixa is a historical region in central Portugal known for its rugged landscapes, traditional villages, and cultural heritage.
  • C. Alto Alentejo
    Alto Alentejo is a subregion in northern Alentejo, Portugal, known for its historic towns, rural landscapes, and traditional agriculture.
  • D. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • E. Baixo Alentejo
    Baixo Alentejo is a sparsely populated, predominantly rural subregion in southern Portugal known for its rolling plains, cork oak forests, and traditional agriculture.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e1de0488190b3639fc25f79d343 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0007757ed48190813f6ab839240a15 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 4:10 a.m.