Triple

T3415021
Position Surface form Disambiguated ID Type / Status
Subject Scala E71988 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: [Scala, influencedBy, Eiffel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eiffel
Context triple: [Scala, influencedBy, Eiffel]
  • A. Eiffel
    Eiffel is a French surname most famously associated with engineer Gustave Eiffel, designer of the Eiffel Tower in Paris.
  • B. 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.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb929b8ec8190aef431ec8ea2cf80 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34be16dd48190a51f4e13a6a13a4f completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.