# Based on a vector with a word sequence, get n-grams (looking forward + backward) If you have annotated your text using `udpipe_annotate`, your text is tokenised in a sequence of words. Based on this vector of words in sequence getting n-grams comes down to looking at the previous/next word and the subsequent previous/next word andsoforth. These words can be `pasted` together to form an n-gram. ```r txt_context(x, n = c(-1, 0, 1), sep = " ", na.rm = FALSE) ``` ## Arguments - `x`: a character vector where each element is just 1 term or word - `n`: an integer vector indicating how many terms to look back and ahead - `sep`: a character element indicating how to `paste` the subsequent words together - `na.rm`: logical, if set to `TRUE`, will keep all text even if it can not look back/ahead the amount specified by `n`. If set to `FALSE`, will have a resulting value of `NA` if at least one element is `NA` or it can not look back/ahead the amount specified by `n`. ## Returns a character vector of the same length of `x` with the n-grams ## Examples ```r x <- c("We", "walked", "anxiously", "to", "the", "doctor", "!") ## Look 1 word before + word itself y <- txt_context(x, n = c(-1, 0), na.rm = FALSE) data.frame(x, y) ## Look 1 word before + word itself + 1 word after y <- txt_context(x, n = c(-1, 0, 1), na.rm = FALSE) data.frame(x, y) y <- txt_context(x, n = c(-1, 0, 1), na.rm = TRUE) data.frame(x, y) ## Look 2 words before + word itself + 1 word after ## even if not all words are there y <- txt_context(x, n = c(-2, -1, 0, 1), na.rm = TRUE, sep = "_") data.frame(x, y) y <- txt_context(x, n = c(-2, -1, 1, 2), na.rm = FALSE, sep = "_") data.frame(x, y) x <- c("We", NA, NA, "to", "the", "doctor", "!") y <- txt_context(x, n = c(-1, 0), na.rm = FALSE) data.frame(x, y) y <- txt_context(x, n = c(-1, 0), na.rm = TRUE) data.frame(x, y) library(data.table) data(brussels_reviews_anno, package = "udpipe") x <- as.data.table(brussels_reviews_anno) x <- subset(x, doc_id %in% txt_sample(unique(x$doc_id), n = 10)) x <- x[, context := txt_context(lemma), by = list(doc_id, sentence_id)] head(x, 20) x$term <- sprintf("%s/%s", x$lemma, x$upos) x <- x[, context := txt_context(term), by = list(doc_id, sentence_id)] head(x, 20) ``` ## See Also `txt_paste`, `txt_next`, `txt_previous`, `shift`

txt_context function