Triple

T13909811
Position Surface form Disambiguated ID Type / Status
Subject Centro Region of Portugal E334459 entity
Predicate containsCity P294 FINISHED
Object Caldas da Rainha E407728 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: Caldas da Rainha | Statement: [Centro Region of Portugal, containsCity, Caldas da Rainha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caldas da Rainha
Context triple: [Centro Region of Portugal, containsCity, Caldas da Rainha]
  • A. Caldas da Rainha chosen
    Caldas da Rainha is a historic spa and market city in western Portugal, renowned for its thermal baths, ceramics tradition, and proximity to the Atlantic coast.
  • B. Alcobaça
    Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
  • C. Vila do Conde
    Vila do Conde is a coastal city in northern Portugal known for its historic shipbuilding heritage, beaches, and well-preserved medieval architecture.
  • D. Lousã
    Lousã is a town and municipality in central Portugal known for its surrounding mountains, schist villages, and outdoor activities such as hiking and mountain biking.
  • E. Lourinhã
    Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2721ec6c8190888f4a9d004eb8e0 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfcd67f081909f97bcf38d814a13 completed May 9, 2026, 5:02 a.m.
Created at: April 9, 2026, 10:16 p.m.