Triple

T15705204
Position Surface form Disambiguated ID Type / Status
Subject Borba Municipality E380690 entity
Predicate region P40 FINISHED
Object Alentejo Central E221591 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: Alentejo Central | Statement: [Borba Municipality, region, Alentejo Central]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alentejo Central
Context triple: [Borba Municipality, region, Alentejo Central]
  • A. Alentejo Central chosen
    Alentejo Central is a subregion in southern Portugal known for its historic towns, rolling plains, and wine production within the broader Alentejo region.
  • B. Alto Alentejo
    Alto Alentejo is a subregion in northern Alentejo, Portugal, known for its historic towns, rural landscapes, and traditional agriculture.
  • C. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • D. 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.
  • E. Alentejo Litoral
    Alentejo Litoral is a coastal subregion of Portugal’s Alentejo known for its Atlantic beaches, rural landscapes, 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f6fc3608190a85b25755f5345db completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00b274fa3481908b019036cd2ae627 completed May 10, 2026, 4:29 p.m.
Created at: April 10, 2026, 4:45 a.m.