Triple

T109726
Position Surface form Disambiguated ID Type / Status
Subject A22 motorway E2219 entity
Predicate serves P98 FINISHED
Object Faro 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 | Statement: [A22 motorway, serves, Faro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faro
Context triple: [A22 motorway, serves, Faro]
  • 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. Kutaisi
    Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
  • C. Furnes (Veurne)
    Furnes (Veurne) is a historic town in West Flanders, Belgium, known for its well-preserved medieval architecture and role as a regional cultural center.
  • D. Halve Maen
    Halve Maen was a Dutch East India Company ship best known for carrying English explorer Henry Hudson on his 1609 voyage that led to the European exploration of the river now called the Hudson River.
  • E. Iceland
    Iceland is a Nordic island nation in the North Atlantic known for its dramatic volcanic landscapes, geothermal activity, and high standard of living.
  • 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_69a24fcdaeb48190a2d796677e4b3281 completed Feb. 28, 2026, 2:15 a.m.
NER Named-entity recognition batch_69a256ce54b48190a3337f5f45d82859 completed Feb. 28, 2026, 2:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69a275e92ed08190819ad8385200dfa6 completed Feb. 28, 2026, 4:58 a.m.
Created at: Feb. 28, 2026, 2:20 a.m.