% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lexical_analysis.R
\name{spacy_lemmatize}
\alias{spacy_lemmatize}
\title{Lemmatize Texts with spaCy}
\usage{
spacy_lemmatize(x, batch_size = 100, model = "en_core_web_sm")
}
\arguments{
\item{x}{Character vector of texts OR a quanteda tokens object.}

\item{batch_size}{Integer; batch size for processing (default: 100).}

\item{model}{Character; spaCy model to use (default: "en_core_web_sm").}
}
\value{
A data frame with columns: doc_id, token_id, token, lemma.
}
\description{
Perform lemmatization using spaCy with optimized pipeline settings.
Disables unnecessary components (NER, parser) for faster processing.
}
\details{
This function disables NER, entity_ruler, and parser components to speed up
lemmatization. Use this for lemmas without other annotations.
}
\concept{lexical}
