Triple

T698048
Position Surface form Disambiguated ID Type / Status
Subject Georges Seurat E13936 entity
Predicate notableWork P4 FINISHED
Object The Eiffel Tower E1351 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: The Eiffel Tower | Statement: [Georges Seurat, notableWork, The Eiffel Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Eiffel Tower
Context triple: [Georges Seurat, notableWork, The Eiffel Tower]
  • A. Eiffel Tower chosen
    The Eiffel Tower is a wrought-iron lattice tower in Paris, France, and one of the most recognizable landmarks and symbols of the country.
  • B. Eiffel
    Eiffel is a French surname most famously associated with engineer Gustave Eiffel, designer of the Eiffel Tower in Paris.
  • C. 58 Tour Eiffel
    58 Tour Eiffel is a contemporary French restaurant located on the first floor of the Eiffel Tower, offering panoramic views of Paris.
  • D. Trocadéro
    Trocadéro is a prominent area in Paris known for its grand esplanade and panoramic views of the Eiffel Tower, historically associated with major exhibitions and cultural events.
  • E. Tokyo Tower
    Tokyo Tower is a landmark red-and-white communications and observation tower in central Tokyo, famous for its city views and Eiffel Tower-inspired design.
  • 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_69a493406c408190957eeec9048a8fb6 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a0c99be48190babc37c397b6a186 completed March 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcac4e9c8190bb6903916a6624a8 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.