Triple

T2651135
Position Surface form Disambiguated ID Type / Status
Subject Olhos de Água E53899 entity
Predicate near P350 FINISHED
Object Albufeira E580 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: Albufeira | Statement: [Olhos de Água, near, Albufeira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albufeira
Context triple: [Olhos de Água, near, Albufeira]
  • A. Albufeira chosen
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • B. Vilamoura
    Vilamoura is a major Portuguese resort town in the Algarve, known for its large marina, golf courses, beaches, and upscale tourist facilities.
  • C. 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.
  • D. Tavira
    Tavira is a historic coastal town in Portugal’s Algarve region, known for its picturesque old town, Roman bridge, and nearby island beaches.
  • E. Praia da Luz
    Praia da Luz is a popular seaside resort village in Portugal’s Algarve region, known for its sandy beach, cliffs, and tourist-oriented waterfront.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd92f5f508190b4ca396c3f399e93 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d3d6a54819090068ef1807ca921 completed March 10, 2026, 1:31 p.m.
Created at: March 6, 2026, 9:53 p.m.