Triple

T15028805
Position Surface form Disambiguated ID Type / Status
Subject Pampilhosa da Serra E378286 entity
Predicate borderedBy P224 FINISHED
Object Covilhã E337094 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: Covilhã | Statement: [Pampilhosa da Serra, borderedBy, Covilhã]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Covilhã
Context triple: [Pampilhosa da Serra, borderedBy, Covilhã]
  • A. Covilhã chosen
    Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
  • B. Montemor-o-Novo
    Montemor-o-Novo is a historic town and municipality in Portugal’s Alentejo region, known for its medieval castle ruins and 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. Lourinhã
    Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
  • E. Sernancelhe
    Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e0e8c88190ac6f5786b4d4040f completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f24967c8190b0bdb84b88a0aaa3 completed May 9, 2026, 4:21 p.m.
Created at: April 10, 2026, 2:58 a.m.