User:PeterMatthew9/Choose an Article

Article Selection
Please list articles that you're considering for your Wikipedia assignment below. Begin to critique these articles and find relevant sources.

Option 1

 * Article title:Inflection
 * Article Evaluation:The article explores linguistic inflection, a process modifying words for grammatical features. It covers types of inflection, examples in English, regular vs. irregular forms, and declension/conjugation patterns. The distinction between analytic and synthetic languages is discussed, along with inflectional paradigms. The article also touches on inflectional morphology, offering examples from various languages. It notes the evolution of English from a moderately inflected language to a weakly inflected one.
 * Sources:Inflection

Option 2

 * Article title:Natural language
 * Article Evaluation:The article discusses natural languages, emphasizing their organic development in human communities without conscious planning. It contrasts them with artificial languages, highlights controlled subsets like Simplified Technical English, and notes the intentional creation of constructed languages like Esperanto. The article briefly mentions creole languages and provides additional topics in the "See also" section. References include John Lyons' book and a historical overview of international languages.
 * Sources:Natural language

Option 3

 * Article title:Inflection
 * Article Evaluation:The article discusses blends in linguistics, particularly the concept of portmanteau words formed by combining sounds and meanings of two or more words intentionally. Examples like "smog" and "motel" are provided, and the article distinguishes blends from contractions and compounds. It delves into morphotactic, morphonological, and morphosemantic classifications of blends, explaining total and partial blends, as well as overlapping and non-overlapping blends. The article also explores attributive and coordinate blends and provides examples. The section on blending of roots is briefly discussed, and lexical selection errors in blending are mentioned. Overall, the article offers a comprehensive exploration of blends in linguistics.
 * Sources:Inflection

Option 4

 * Article title:Natural language
 * Article Evaluation:This article introduces the concept of sentence embeddings in natural language processing (NLP). Sentence embeddings are numeric representations of sentences as vectors of real numbers, encoding meaningful semantic information. The state-of-the-art embeddings are based on dedicated sentence transformer models, with BERT being a pioneering model. The article discusses the shortcomings of BERT's [CLS] token approach and introduces SBERT, which achieves superior sentence embedding performance through fine-tuning on the SNLI dataset using a siamese neural network architecture. Other approaches involve distributional semantics, such as Skip-Thought, and aggregating word embeddings into sentence embeddings, like continuous bag-of-words (CBOW) or vector of locally aggregated word embeddings (VLAWE). The applications of sentence embeddings include natural language queryable knowledge bases for semantic search. LangChain, for example, utilizes sentence transformers to index documents, allowing for efficient retrieval of relevant information. Additionally, sentence embeddings are used for sentence similarity evaluation, aiding in optimizing large language models' generation parameters.  The article evaluates sentence embeddings using the Sentences Involving Compositional Knowledge (SICK) corpus, measuring entailment and relatedness. It highlights the success of certain models, such as a BiLSTM network trained on the Stanford Natural Language Inference (SNLI) Corpus. Overall, the article provides an overview of the current state of sentence embeddings, their applications, and evaluation methods in the field of natural language processing.
 * Sources:Natural language