Triple

T19925303
Position Surface form Disambiguated ID Type / Status
Subject E4 European long-distance path E478906 entity
Predicate startingPoint P389 FINISHED
Object Tarifa 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: Tarifa | Statement: [E4 European long-distance path, startingPoint, Tarifa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarifa
Context triple: [E4 European long-distance path, startingPoint, Tarifa]
  • A. Tarifa
    Tarifa is a rural parish within Samborondón Canton in Ecuador’s Guayas Province.
  • B. Tarifa chosen
    Tarifa is a coastal town in southern Spain known as the southernmost point of mainland Europe and a major destination for wind sports like kitesurfing and windsurfing.
  • C. Marbella
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • D. Benalmádena
    Benalmádena is a coastal resort town on Spain’s Costa del Sol, known for its beaches, marina, and tourist attractions near Málaga.
  • E. Torremolinos
    Torremolinos is a popular seaside resort town on Spain’s Costa del Sol, known for its beaches, nightlife, and tourism-focused economy.
  • 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e659c992fc8190bd262d528be0e636 completed April 20, 2026, 4:52 p.m.
Created at: April 10, 2026, 1:53 p.m.