Triple

T16280348
Position Surface form Disambiguated ID Type / Status
Subject Bertil, Duke of Halland E395246 entity
Predicate givenName P17 FINISHED
Object Eugén E305910 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: Eugén | Statement: [Bertil, Duke of Halland, givenName, Eugén]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eugén
Context triple: [Bertil, Duke of Halland, givenName, Eugén]
  • A. Eugen chosen
    Eugen is a masculine given name of Greek origin, commonly used in various European languages and derived from a word meaning "well-born" or "noble."
  • B. Eugen
    Eugen is the given first name of the influential German playwright and poet Bertolt Brecht.
  • C. Eduard
    Eduard is a central character in Paulo Coelho’s novel "Veronika Decides to Die," portrayed as a sensitive, introspective young man whose relationship with the protagonist profoundly influences her view of life and death.
  • D. Eduard
    Eduard is a masculine given name of German origin, commonly used in various European countries.
  • E. Eduard
    Eduard is one of the central protagonists in Johann Wolfgang von Goethe’s novel "Elective Affinities," whose actions and relationships drive the story’s exploration of passion, marriage, and moral conflict.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24611926c81909b276ca3f406f15d completed April 17, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c48e5c8190a387a4158362417a completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.