Triple

T3110917
Position Surface form Disambiguated ID Type / Status
Subject Tavira railway station E64947 entity
Predicate serves P98 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: [Tavira railway station, serves, Tavira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tavira
Context triple: [Tavira railway station, serves, 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. Carvoeiro
    Carvoeiro is a picturesque coastal village in southern Portugal known for its dramatic cliffs, sandy beaches, and role as a popular holiday destination.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43954f0819096a96331bf3c53a8 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b2a9b648190a74c7691cc7a4959 completed March 12, 2026, 5:12 a.m.
Created at: March 8, 2026, 3:04 p.m.