Triple

T2397066
Position Surface form Disambiguated ID Type / Status
Subject Count of Vidigueira E47674 entity
Predicate region P40 FINISHED
Object Alentejo 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 | Statement: [Count of Vidigueira, region, Alentejo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alentejo
Context triple: [Count of Vidigueira, region, Alentejo]
  • 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. Algarve
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8c4a8bc819086892a75caac0207 completed March 7, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1f84a88388190af50c6861c635383 completed March 11, 2026, 11:18 p.m.
Created at: March 4, 2026, 7:57 p.m.