Triple

T15759259
Position Surface form Disambiguated ID Type / Status
Subject Arraiolos Municipality E382049 entity
Predicate locatedIn P40 FINISHED
Object Alentejo region E38350 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 region | Statement: [Arraiolos Municipality, locatedIn, Alentejo region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alentejo region
Context triple: [Arraiolos Municipality, locatedIn, Alentejo region]
  • A. Alentejo chosen
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • B. Alto Alentejo
    Alto Alentejo is a subregion in northern Alentejo, Portugal, known for its historic towns, rural landscapes, and traditional agriculture.
  • C. Alentejo Central
    Alentejo Central is a subregion in southern Portugal known for its historic towns, rolling plains, and wine production within the broader Alentejo region.
  • D. Alentejo Litoral
    Alentejo Litoral is a coastal subregion of Portugal’s Alentejo known for its Atlantic beaches, rural landscapes, and traditional agriculture.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b35ea48190a758ee76a57b5451 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01232399008190b23dfaec237563ef completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 4:47 a.m.