Triple

T1746751
Position Surface form Disambiguated ID Type / Status
Subject Portimão E38351 entity
Predicate countrySubdivision P766 FINISHED
Object Region Algarve E6079 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: Region Algarve | Statement: [Portimão, countrySubdivision, Region Algarve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Region Algarve
Context triple: [Portimão, countrySubdivision, Region Algarve]
  • A. Algarve chosen
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • B. Alentejo Litoral
    Alentejo Litoral is a coastal subregion of Portugal’s Alentejo known for its Atlantic beaches, 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. Alto Alentejo
    Alto Alentejo is a subregion in northern Alentejo, Portugal, known for its historic towns, rural landscapes, and traditional agriculture.
  • E. northeastern Portugal
    Northeastern Portugal is a culturally distinct, sparsely populated region bordering Spain, known for its Mirandese-speaking communities, traditional rural landscapes, and historic towns.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63eabdf48190878ecde3d1b1faf3 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae651c82588190b9f1461a7e135670 completed March 9, 2026, 6:13 a.m.
Created at: March 4, 2026, 7:31 p.m.