Triple

T7269955
Position Surface form Disambiguated ID Type / Status
Subject EN125 road E161074 entity
Predicate connects P390 FINISHED
Object Olhão E63889 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: Olhão | Statement: [EN125 road, connects, Olhão]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olhão
Context triple: [EN125 road, connects, Olhão]
  • A. Olhão chosen
    Olhão is a coastal city in Portugal’s Algarve region, known for its fishing port, historic waterfront, and access to the Ria Formosa lagoon and nearby islands.
  • B. Ferragudo
    Ferragudo is a picturesque coastal village in Portugal’s Algarve region, known for its traditional whitewashed houses, fishing heritage, and scenic beaches along the Arade River.
  • C. Estepona
    Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
  • D. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • E. Marbella
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae9f8bc8190a8c31cc29926919c completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e52b8ea0819096c331f78dee5e4b completed March 28, 2026, 2:26 p.m.
Created at: March 27, 2026, 2:58 p.m.