Triple

T6438961
Position Surface form Disambiguated ID Type / Status
Subject Formentera E129969 entity
Predicate connectedByFerryTo P1831 FINISHED
Object Denia E425416 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: Denia | Statement: [Formentera, connectedByFerryTo, Denia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denia
Context triple: [Formentera, connectedByFerryTo, Denia]
  • A. Denia chosen
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • B. Benidorm
    Benidorm is a major Spanish Mediterranean resort city famous for its skyscraper-lined beaches, vibrant nightlife, and mass tourism.
  • C. Pietrasanta
    Pietrasanta is a historic Tuscan town in Italy renowned for its marble workshops, sculpture studios, and vibrant community of international artists.
  • D. Pietrasanta
    Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
  • E. Pollença
    Pollença is a historic town in northern Mallorca, Spain, known for its charming stone streets, traditional architecture, and proximity to scenic coastal and mountain landscapes.
  • 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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06965a5d48190a5860da9e22dc6e0 completed March 22, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c669de36a08190837817b32074e405 completed March 27, 2026, 11:28 a.m.
Created at: March 22, 2026, 4:45 p.m.