Triple

T3609021
Position Surface form Disambiguated ID Type / Status
Subject Beira Litoral E76438 entity
Predicate includesCity P3207 FINISHED
Object Penacova E431642 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: Penacova | Statement: [Beira Litoral, includesCity, Penacova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penacova
Context triple: [Beira Litoral, includesCity, Penacova]
  • A. Penacova chosen
    Penacova is a picturesque riverside town in central Portugal known for its scenic landscapes, viewpoints, and traditional villages along the Mondego River.
  • B. Torres Novas
    Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
  • C. Mértola
    Mértola is a historic riverside town and municipality in southeastern Portugal known for its well-preserved medieval architecture and rich Islamic and Roman heritage.
  • D. Lourinhã
    Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
  • E. Covilhã
    Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
  • 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_69ad85da0ba481908b3b48c69efe2b98 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc22a3cf081908c20b6fb55be0db2 completed March 8, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6786a558819098973b8f10b7e7cb completed March 20, 2026, 3:28 p.m.
Created at: March 8, 2026, 3:22 p.m.