Triple

T2328012
Position Surface form Disambiguated ID Type / Status
Subject Naomi E48334 entity
Predicate usedIn P98 FINISHED
Object German language E9053 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: German language | Statement: [Naomi, usedIn, German language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German language
Context triple: [Naomi, usedIn, German language]
  • A. German chosen
    German is a West Germanic language widely spoken in Central Europe and used as an official language in several countries, including Germany, Austria, Switzerland, and Luxembourg.
  • B. Deutch
    Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
  • C. Alemannic German
    Alemannic German is a group of Upper German dialects spoken primarily in parts of Switzerland, Germany, Austria, and Liechtenstein.
  • D. Palatine German
    Palatine German is a West Central German dialect spoken primarily in the Palatinate region of southwestern Germany and parts of the United States, notably among Pennsylvania Dutch communities.
  • E. Rhenish Franconian
    Rhenish Franconian is a group of West Central German dialects spoken primarily in parts of western Germany, Luxembourg, and eastern France.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc64c7f1881909b0d847f7782e803 completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae897243c48190a18b0e02ad664ead completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:50 p.m.