Triple

T7278439
Position Surface form Disambiguated ID Type / Status
Subject Tilsit E163087 entity
Predicate languageHistoricallySpoken P1434 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: [Tilsit, languageHistoricallySpoken, German]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German
Context triple: [Tilsit, languageHistoricallySpoken, German]
  • 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. German
    German refers to a person belonging to the ethnic group native to Germany, typically associated with the German language and culture.
  • C. Deutch
    Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
  • D. Alemannic German
    Alemannic German is a group of Upper German dialects spoken primarily in parts of Switzerland, Germany, Austria, and Liechtenstein.
  • E. Standard German
    Standard German is the standardized variety of the German language used in formal communication, education, media, and official contexts across German-speaking 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb3251808190bd9da71bc183c945 completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db3450208190b67e4329a531ad0c completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:59 p.m.