Triple

T21959579
Position Surface form Disambiguated ID Type / Status
Subject A23 motorway (Portugal) E542287 entity
Predicate startPoint P389 FINISHED
Object Torres Novas NE NERFINISHED

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: Torres Novas | Statement: [A23 motorway (Portugal), startPoint, Torres Novas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torres Novas
Context triple: [A23 motorway (Portugal), startPoint, Torres Novas]
  • A. Torres Novas chosen
    Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
  • B. 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.
  • C. Carcavelos
    Carcavelos is a coastal town in the Lisbon metropolitan area of Portugal, known for its popular sandy beach and strong surfing conditions along the Estoril coastline.
  • D. Montalegre
    Montalegre is a town in northern Portugal known for its historic castle, traditional rural culture, and role as the seat of Montalegre Municipality in the Trás-os-Montes region.
  • 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 (2 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12454a290819094d4b56547816e3f completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8 p.m.