Triple

T22744507
Position Surface form Disambiguated ID Type / Status
Subject Montgat E562510 entity
Predicate region P40 FINISHED
Object Maresme coast NE NERFINISHED

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: Maresme coast | Statement: [Montgat, region, Maresme coast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maresme coast
Context triple: [Montgat, region, Maresme coast]
  • A. Maresme chosen
    Maresme is a coastal comarca in Catalonia, Spain, known for its Mediterranean beaches, mild climate, and proximity to Barcelona.
  • B. Murcian coast
    The Murcian coast is a stretch of southeastern Spain’s Mediterranean shoreline known for its warm climate, sandy beaches, and distinctive coastal lagoon landscapes.
  • C. Andalusian coast
    The Andalusian coast is the long, strategically important stretch of southern Spain’s shoreline along the Atlantic Ocean and Mediterranean Sea, including areas such as the Costa del Sol and the Bay of Cádiz.
  • D. Salacak coast
    Salacak coast is a scenic waterfront area on Istanbul’s Asian side, offering prominent views of the Maiden’s Tower and the Bosphorus.
  • E. Loulé coastline
    The Loulé coastline is a scenic stretch of southern Portugal’s Algarve shore known for its long sandy beaches, dramatic red and ochre cliffs, and popular resort areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797590f08190a784f73fcd27b101 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.