Triple

T1268840
Position Surface form Disambiguated ID Type / Status
Subject N125 road E15663 entity
Predicate connects P390 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: [N125 road, connects, Faro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faro
Context triple: [N125 road, connects, 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. Hvalsey
    Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
  • E. Stromness
    Stromness is a historic harbor town on the southwest coast of Orkney Mainland in Scotland, known for its stone-built waterfront and maritime heritage.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c03aaa8c8190bacb7de5a38329da completed March 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69acacb5b8888190aa969c0d8cc3fd0d completed March 7, 2026, 10:54 p.m.
Created at: March 1, 2026, 7:50 p.m.