Triple

T13180439
Position Surface form Disambiguated ID Type / Status
Subject Ursula E313707 entity
Predicate hasLanguageOfUse P207 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: [Ursula, hasLanguageOfUse, German language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German language
Context triple: [Ursula, hasLanguageOfUse, German language]
  • A. German
    German refers to a person belonging to the ethnic group native to Germany, typically associated with the German language and culture.
  • B. 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.
  • C. German ICE
    The German ICE (InterCity Express) is Germany’s high-speed train system, known for its fast, comfortable long-distance rail service and advanced engineering.
  • D. Deutsch
    Deutsch is a surname of German origin borne by numerous individuals across various fields, including arts, sciences, and public life.
  • E. Deutch
    Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c490ed081908ea54edb25c3de90 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5ee66188190afb75a598a2f8211 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:14 p.m.