Triple

T5815254
Position Surface form Disambiguated ID Type / Status
Subject Lisbon District E128968 entity
Predicate contains P35 FINISHED
Object Lourinhã E438500 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: Lourinhã | Statement: [Lisbon District, contains, Lourinhã]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lourinhã
Context triple: [Lisbon District, contains, Lourinhã]
  • A. Lourinhã chosen
    Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
  • B. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • C. Lamego
    Lamego is a historic city in northern Portugal known for its baroque Sanctuary of Our Lady of Remedies and its location in the Douro wine region.
  • D. Torres Novas
    Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
  • E. Caldas da Rainha
    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.
  • 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_69c0084788848190bcf71f6bc5d71597 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0336344148190bcf417c0b9617cb9 completed March 22, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c603c7dac48190b742e9e5430b8bde completed March 27, 2026, 4:12 a.m.
Created at: March 22, 2026, 3:53 p.m.