Triple

T16161874
Position Surface form Disambiguated ID Type / Status
Subject Galeries Lafayette Haussmann E392197 entity
Predicate hasViewOf P854 FINISHED
Object 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: Eiffel Tower | Statement: [Galeries Lafayette Haussmann, hasViewOf, Eiffel Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eiffel Tower
Context triple: [Galeries Lafayette Haussmann, hasViewOf, 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. Eiffel
    Eiffel is an object-oriented programming language designed by Bertrand Meyer, known for its emphasis on software correctness through the Design by Contract methodology.
  • D. Iron Tower
    The Iron Tower is a historic medieval watchtower and former city gate located in Mainz, Germany.
  • E. 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.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21e5ffba88190b9dc7bb9afb6fdf2 completed April 17, 2026, 11:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7b33f3481909fe856b8be7d9bcd completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:02 a.m.