Triple

T3715020
Position Surface form Disambiguated ID Type / Status
Subject de Lannoy E81506 entity
Predicate hasSpellingVariant P457 FINISHED
Object De Lannoy E81506 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: De Lannoy | Statement: [de Lannoy, hasSpellingVariant, De Lannoy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De Lannoy
Context triple: [de Lannoy, hasSpellingVariant, De Lannoy]
  • A. de Lannoy chosen
    De Lannoy is a European-origin surname historically associated with noble lineages and later anglicized in America as "Delano," notably borne by ancestors of U.S. President Franklin Delano Roosevelt.
  • B. Le Clercq
    Le Clercq is the surname of Tanaquil Le Clercq, the renowned mid-20th-century American ballerina associated with the New York City Ballet.
  • C. Jan D'Alquen
    Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
  • D. Benoit Dageville
    Benoit Dageville is a French computer scientist and entrepreneur best known as a co-founder of the cloud data platform company Snowflake.
  • E. Frank Schoonover
    Frank Schoonover was an American illustrator associated with the Brandywine School, renowned for his adventure, Western, and historical paintings in early 20th-century magazines and books.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9ce253c8190ada8eaa395fd3d5c completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce0f690c819091d9caf9271f9bbd completed March 14, 2026, 2:55 a.m.
Created at: March 8, 2026, 3:33 p.m.