Triple

T14336139
Position Surface form Disambiguated ID Type / Status
Subject Nobu restaurants E355470 entity
Predicate hasLocation P40 FINISHED
Object Mykonos E71781 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: Mykonos | Statement: [Nobu restaurants, hasLocation, Mykonos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mykonos
Context triple: [Nobu restaurants, hasLocation, Mykonos]
  • A. Mykonos chosen
    Mykonos is a popular Greek island in the Cyclades known for its whitewashed architecture, vibrant nightlife, and picturesque beaches.
  • B. Paros
    Paros is a popular Greek island in the central Aegean known for its traditional Cycladic villages, beaches, and marble quarries.
  • C. Skiathos
    Skiathos is a small Greek island in the northwest Aegean Sea, renowned for its sandy beaches, pine forests, and vibrant tourist resorts.
  • D. Skopelos
    Skopelos is a Greek island in the western Aegean Sea, known for its lush pine forests, traditional whitewashed villages, and scenic beaches.
  • E. Karpathos
    Karpathos is a Greek island in the southeastern Aegean Sea known for its rugged mountains, traditional villages, and clear, windswept beaches popular with windsurfers.
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8c2241e48190a0c626b3d741966a completed April 14, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0170d8c9f0819099a398814f49f0ed completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 1:14 a.m.