Triple

T21372610
Position Surface form Disambiguated ID Type / Status
Subject Ulrik Huber E527106 entity
Predicate givenName P17 FINISHED
Object Ulrik 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: Ulrik | Statement: [Ulrik Huber, givenName, Ulrik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulrik
Context triple: [Ulrik Huber, givenName, Ulrik]
  • A. Ulrik chosen
    Ulrik is a masculine given name of Scandinavian origin, commonly used in countries like Denmark and Norway and related to the German name Ulrich.
  • B. Søren
    Søren is a masculine given name of Scandinavian origin, most famously borne by the Danish philosopher Søren Kierkegaard.
  • C. Henrik
    Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
  • D. Eskil
    Eskil is a town and district in central Turkey known for its location within Aksaray Province on the Central Anatolian plateau.
  • E. Johan
    Johan is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0b0d5ec81908da8f38380dbdc7a completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.