Triple

T11409024
Position Surface form Disambiguated ID Type / Status
Subject Teodoor E270316 entity
Predicate hasAlternativeSpelling P457 FINISHED
Object Teodor E270314 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: Teodor | Statement: [Teodoor, hasAlternativeSpelling, Teodor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teodor
Context triple: [Teodoor, hasAlternativeSpelling, Teodor]
  • A. Teodor chosen
    Teodor is a given name, commonly used in various European languages, that corresponds to the English name Theodore.
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Theodor
    Theodor is the given name of Emil Theodor Kocher, a Swiss surgeon and Nobel laureate renowned for his pioneering work in thyroid surgery.
  • D. 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.
  • E. Eduard
    Eduard is a masculine given name of German origin, commonly used in various European countries.
  • 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8014e72748190a01bde2f0105cedb completed April 9, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e603e6614c8190b61691bd933fa529 completed April 20, 2026, 10:45 a.m.
Created at: April 8, 2026, 9:34 p.m.