Triple

T2313765
Position Surface form Disambiguated ID Type / Status
Subject Yukihiro Matsumoto E51015 entity
Predicate influencedBy P9 FINISHED
Object Eiffel E96205 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 | Statement: [Yukihiro Matsumoto, influencedBy, Eiffel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eiffel
Context triple: [Yukihiro Matsumoto, influencedBy, Eiffel]
  • A. Eiffel chosen
    Eiffel is an object-oriented programming language designed by Bertrand Meyer, known for its emphasis on software correctness through the Design by Contract methodology.
  • B. Eiffel
    Eiffel is a French surname most famously associated with engineer Gustave Eiffel, designer of the Eiffel Tower in Paris.
  • C. Eiffel Tower
    The Eiffel Tower is a wrought-iron lattice tower in Paris, France, and one of the most recognizable landmarks and symbols of the country.
  • 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. 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61c1ef08190911d5f58c2e91189 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae895f5420819087b403e9772dce9a completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:49 p.m.