Triple

T4255569
Position Surface form Disambiguated ID Type / Status
Subject Sierre E95964 entity
Predicate officialLanguage 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: [Sierre, officialLanguage, German]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German
Context triple: [Sierre, officialLanguage, 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec1971c81908f7a72418efa8bcc completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a88a68f081909e5bae5b0414f534 completed March 14, 2026, 6:27 p.m.
Created at: March 12, 2026, 11:06 p.m.