Triple

T11725945
Position Surface form Disambiguated ID Type / Status
Subject Vila Viçosa E278767 entity
Predicate locatedIn P40 FINISHED
Object Alentejo Central Subregion 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 Subregion | Statement: [Vila Viçosa, locatedIn, Alentejo Central Subregion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alentejo Central Subregion
Context triple: [Vila Viçosa, locatedIn, Alentejo Central Subregion]
  • 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. 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.
  • D. Alentejo Litoral
    Alentejo Litoral is a coastal subregion of Portugal’s Alentejo known for its Atlantic beaches, rural landscapes, and traditional agriculture.
  • E. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4d70d908190b5f47c2ef501a191 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f09004c5908190bd6d7a29b266318b completed April 28, 2026, 10:46 a.m.
Created at: April 8, 2026, 9:41 p.m.