Triple

T288133
Position Surface form Disambiguated ID Type / Status
Subject CET E5929 entity
Predicate usedByCountry P715 FINISHED
Object San Marino E19129 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: San Marino | Statement: [CET, usedByCountry, San Marino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Marino
Context triple: [CET, usedByCountry, San Marino]
  • A. San Marino chosen
    San Marino is a small, landlocked microstate surrounded by Italy, known as one of the world’s oldest republics and a popular tourist destination.
  • B. Vatican City
    Vatican City is an independent city-state enclaved within Rome that serves as the spiritual and administrative headquarters of the Roman Catholic Church and the residence of the Pope.
  • C. Monaco
    Monaco is a small sovereign city-state on the French Riviera known for its wealth, luxury tourism, and status as a major tax haven and gambling hub.
  • D. Andorra
    Andorra is a small, landlocked principality in the eastern Pyrenees between France and Spain, known for its mountainous terrain, tourism, and status as a tax haven.
  • E. Malta
    Malta is a small island nation in the central Mediterranean known for its rich history, strategic location, and membership in the European Union.
  • 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_69a25946a7ac8190a78871c210213272 completed Feb. 28, 2026, 2:56 a.m.
NER Named-entity recognition batch_69a260d21e5881909f3baba8b8dfff92 completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a4853de9708190bd7156ef097bde29 completed March 1, 2026, 6:28 p.m.
Created at: Feb. 28, 2026, 3:02 a.m.