Triple

T11078952
Position Surface form Disambiguated ID Type / Status
Subject Daniel Kottke E261937 entity
Predicate familyName P18 FINISHED
Object Kottke E261937 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: Kottke | Statement: [Daniel Kottke, familyName, Kottke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kottke
Context triple: [Daniel Kottke, familyName, Kottke]
  • A. Kottke chosen
    Kottke is a surname most notably associated with individuals such as Daniel Kottke, an early Apple employee and friend of Steve Jobs.
  • B. Kuttner
    Kuttner is a surname of German origin borne by various notable individuals across fields such as literature, politics, and academia.
  • C. Blodget
    Blodget is a surname that serves as a variant spelling of Blodgett, associated with various individuals and families, particularly in English-speaking countries.
  • D. Kovach
    Kovach is a surname of Eastern European origin, commonly found among people of Hungarian or Slavic descent and often representing an anglicized form of similar regional names.
  • E. Digerati
    Digerati is a book by literary agent and author John H. Brockman that profiles influential thinkers and innovators from the early digital and internet culture.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799953d58819096b645a1377e70f2 completed April 9, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8d4f22881909fa3d094a19b0a14 completed April 18, 2026, 6:09 p.m.
Created at: April 8, 2026, 9:27 p.m.