Triple

T21067587
Position Surface form Disambiguated ID Type / Status
Subject Theo LeSieg E519016 entity
Predicate alsoKnownAs P39 FINISHED
Object Theo Le Sieg NE NERFINISHED

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: Theo Le Sieg | Statement: [Theo LeSieg, alsoKnownAs, Theo Le Sieg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theo Le Sieg
Context triple: [Theo LeSieg, alsoKnownAs, Theo Le Sieg]
  • A. Theo LeSieg chosen
    Theo LeSieg is a pen name used by beloved children's author Dr. Seuss for books he wrote but did not illustrate himself.
  • B. Lorenz von Stein
    Lorenz von Stein was a 19th-century German economist, sociologist, and public administration scholar known for his influential work on the modern state, social reform, and the relationship between class struggle and government.
  • C. Paul Weigel
    Paul Weigel was a German-born American character actor active in early 20th-century cinema, appearing in numerous silent and early sound films.
  • D. William Sieghart
    William Sieghart is a British entrepreneur, publisher, and philanthropist best known for championing poetry and the arts in the UK, including founding major poetry initiatives and prizes.
  • E. Achim von Borries
    Achim von Borries is a German film director and screenwriter known for co-creating acclaimed projects such as the television series "Babylon Berlin."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b505ef108190b25dd4033e2ff7eb completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6feb5772481909e32af3b3a69df76 completed April 21, 2026, 4:36 a.m.
Created at: April 16, 2026, 2:45 p.m.