Triple

T695423
Position Surface form Disambiguated ID Type / Status
Subject Tavira E13884 entity
Predicate locatedIn P40 FINISHED
Object Faro District E6080 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: Faro District | Statement: [Tavira, locatedIn, Faro District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faro District
Context triple: [Tavira, locatedIn, Faro District]
  • A. Faro District chosen
    Faro District is the southernmost administrative district of mainland Portugal, encompassing much of the Algarve region and its popular coastal resorts.
  • B. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • C. Lofoten
    Lofoten is a dramatic Arctic archipelago in Norway known for its steep mountains, sheltered bays, fishing villages, and views of the midnight sun and Northern Lights.
  • D. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • E. Faro
    Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
  • 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_69a493406c408190957eeec9048a8fb6 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a0c5f51c8190acc4915099e4b384 completed March 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e376f748190af7088c53605c0cb completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:36 p.m.