Triple

T997913
Position Surface form Disambiguated ID Type / Status
Subject Promenade des Anglais E21536 entity
Predicate touristAttractionIn P7335 FINISHED
Object Nice E2387 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: Nice | Statement: [Promenade des Anglais, touristAttractionIn, Nice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nice
Context triple: [Promenade des Anglais, touristAttractionIn, Nice]
  • A. Nice chosen
    Nice is a prominent Mediterranean coastal city on the French Riviera, known for its mild climate, beaches, and vibrant cultural life.
  • B. Nice Agreement
    The Nice Agreement is an international treaty that establishes a standardized classification system of goods and services used for the registration of trademarks.
  • C. FRIENDLY
    FRIENDLY is the airline callsign used by Southern Airways Express, a U.S.-based commuter and regional airline.
  • D. Nice Classification
    Nice Classification is an international system that categorizes goods and services into standardized classes for the registration of trademarks.
  • E. Nice Carnival
    Nice Carnival is one of the world’s major and oldest carnival festivals, held annually in the French Riviera city of Nice and known for its elaborate parades, floats, and flower battles.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4e0f0d081908b888c246d001786 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3ba52ebc819084e3d003a3ec8417 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:41 p.m.