Triple

T1781594
Position Surface form Disambiguated ID Type / Status
Subject mainland Portugal E39301 entity
Predicate containsCity P294 FINISHED
Object Faro E84088 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 | Statement: [mainland Portugal, containsCity, Faro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faro
Context triple: [mainland Portugal, containsCity, Faro]
  • A. Faro chosen
    Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
  • B. Dokkum
    Dokkum is a historic fortified town in the northern Netherlands, known as one of the Frisian Eleven Cities and for its association with the martyrdom of Saint Boniface.
  • C. Køpmannæhafn
    Køpmannæhafn is the historical Danish name for the city now known as Copenhagen, reflecting its origins as a merchant harbor.
  • D. Lenakel
    Lenakel is an Oceanic language spoken primarily on Tanna Island in Vanuatu.
  • E. Grimstad
    Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e34fe881908aa75f2b4141b87b completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1b8e26c8190af6e45265e2b182f completed March 8, 2026, 7:44 p.m.
Created at: March 4, 2026, 7:31 p.m.