Triple

T4046977
Position Surface form Disambiguated ID Type / Status
Subject Faro E84088 entity
Predicate hasRailConnectionTo P848 FINISHED
Object Tavira E13884 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: Tavira | Statement: [Faro, hasRailConnectionTo, Tavira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tavira
Context triple: [Faro, hasRailConnectionTo, Tavira]
  • A. Tavira chosen
    Tavira is a historic coastal town in Portugal’s Algarve region, known for its picturesque old town, Roman bridge, and nearby island beaches.
  • B. Portimão
    Portimão is a coastal city and popular tourist destination in southern Portugal, known for its beaches, marina, and vibrant waterfront along the Arade River.
  • C. Silves
    Silves is a historic town in southern Portugal known for its well-preserved Moorish castle and former status as the medieval capital of the Algarve region.
  • D. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • E. Marina de Tavira
    Marina de Tavira is a Mexican actress best known internationally for her Academy Award–nominated supporting role in Alfonso Cuarón’s film "Roma."
  • 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb62593c8190ab8462c4d9cd9d08 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b757a4c48190bf72c6852b00777f completed March 14, 2026, 7:30 p.m.
Created at: March 9, 2026, 3:37 p.m.