Extract named entities from texts using spaCy — spacy_extract

This function extracts named entities from texts, based on the entity tag ent attributes of documents objects parsed by spaCy (see https://spacy.io/usage/linguistic-features#section-named-entities).

spacy_extract_entity(
  x,
  output = c("data.frame", "list"),
  type = c("all", "named", "extended"),
  multithread = TRUE,
  ...
)

Arguments

x: a character object or a TIF-compliant corpus data.frame (see https://github.com/ropenscilabs/tif)
output: type of returned object, either "list" or "data.frame".
type: type of named entities, either named, extended, or all. See https://spacy.io/docs/usage/entity-recognition#entity-types for details.
multithread: logical; If TRUE, the processing is parallelized using spaCy's architecture (https://spacy.io/api)
...: unused

Value

either a list or data.frame of tokens

Details

When the option output = "data.frame" is selected, the function returns a data.frame with the following fields.

entity_type: type of entity (e.g. ORG for organizations)
start_id: serial number ID of starting token. This number corresponds with the number of data.frame returned from spacy_tokenize(x) with default options.
length: number of words (tokens) included in a named entity (e.g. for an entity, "New York Stock Exchange"", length = 4)

Examples

if (FALSE) {
spacy_initialize()

txt <- c(doc1 = "The Supreme Court is located in Washington D.C.",
         doc2 = "Paul earned a postgraduate degree from MIT.")
spacy_extract_entity(txt)
spacy_extract_entity(txt, output = "list")
}