Triple

T418345
Position Surface form Disambiguated ID Type / Status
Subject Amish E8043 entity
Predicate language P15 FINISHED
Object Bernese German E17970 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: Bernese German | Statement: [Amish, language, Bernese German]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bernese German
Context triple: [Amish, language, Bernese German]
  • A. Alemannic German chosen
    Alemannic German is a group of Upper German dialects spoken primarily in parts of Switzerland, Germany, Austria, and Liechtenstein.
  • B. Romandy
    Romandy is the French-speaking western region of Switzerland, encompassing cantons such as Geneva, Vaud, Neuchâtel, and Jura.
  • C. Austro-Bavarian German
    Austro-Bavarian German is a major Upper German dialect group spoken primarily in Austria and parts of Bavaria and South Tyrol, characterized by distinct phonology, vocabulary, and regional varieties.
  • D. German
    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.
  • 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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ee9059248190ba901680431914b5 completed Feb. 28, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69a423a4debc819098e13855b550a72e completed March 1, 2026, 11:31 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.