Triple

T6292386
Position Surface form Disambiguated ID Type / Status
Subject Prince's Palace of Monaco E141047 entity
Predicate city P40 FINISHED
Object Monaco E18404 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: Monaco | Statement: [Prince's Palace of Monaco, city, Monaco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monaco
Context triple: [Prince's Palace of Monaco, city, Monaco]
  • A. Monaco chosen
    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.
  • B. AS Monaco
    AS Monaco is a prominent football club based in the Principality of Monaco, known for competing in France's top division and developing numerous world-class players.
  • C. 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.
  • D. San Marino
    San Marino is a small, landlocked microstate surrounded by Italy, known as one of the world’s oldest republics and a popular tourist destination.
  • E. San Marino
    San Marino is a small, affluent residential city in Los Angeles County, California, known for its high-ranking schools and the Huntington Library, Art Museum, and Botanical Gardens.
  • 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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0642017588190b6c99c685653f6c2 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c603f715a08190b44156b4f5166631 completed March 27, 2026, 4:13 a.m.
Created at: March 22, 2026, 4:27 p.m.