Triple

T13114028
Position Surface form Disambiguated ID Type / Status
Subject Märkisch-Oderland E311046 entity
Predicate hasOfficialLanguage P236 FINISHED
Object German 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 | Statement: [Märkisch-Oderland, hasOfficialLanguage, German]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German
Context triple: [Märkisch-Oderland, hasOfficialLanguage, German]
  • 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. Deutsch
    Deutsch is a surname of German origin borne by numerous individuals across various fields, including arts, sciences, and public life.
  • D. Deutch
    Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
  • E. 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.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817f8ee8819084078b4bec5e4f18 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27d8110819087ade3537f867ae0 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:06 p.m.