EntityRuler
The entity ruler lets you add spans to the Doc.ents using
token-based rules or exact phrase matches. It can be combined with the
statistical EntityRecognizer to boost accuracy, or
used on its own to implement a purely rule-based entity recognition system. For
usage examples, see the docs on
rule-based entity recognition.
Assigned Attributes
This component assigns predictions basically the same way as the
EntityRecognizer.
Predictions can be accessed under Doc.ents as a tuple. Each label will also be
reflected in each underlying token, where it is saved in the Token.ent_type
and Token.ent_iob fields. Note that by definition each token can only have one
label.
When setting Doc.ents to create training data, all the spans must be valid and
non-overlapping, or an error will be thrown.
| Location | Value |
|---|---|
Doc.ents | The annotated spans. Tuple[Span] |
Token.ent_iob | An enum encoding of the IOB part of the named entity tag. int |
Token.ent_iob_ | The IOB part of the named entity tag. str |
Token.ent_type | The label part of the named entity tag (hash). int |
Token.ent_type_ | The label part of the named entity tag. str |
Config and implementation
The default config is defined by the pipeline component factory and describes
how the component should be configured. You can override its settings via the
config argument on nlp.add_pipe or in your
config.cfg for training.
| Setting | Description |
|---|---|
phrase_matcher_attr | Optional attribute name match on for the internal PhraseMatcher, e.g. LOWER to match on the lowercase token text. Defaults to None. Optional[Union[int, str]] |
matcher_fuzzy_compare v3.5 | The fuzzy comparison method, passed on to the internal Matcher. Defaults to spacy.matcher.levenshtein.levenshtein_compare. Callable |
validate | Whether patterns should be validated (passed to the Matcher and PhraseMatcher). Defaults to False. bool |
overwrite_ents | If existing entities are present, e.g. entities added by the model, overwrite them by matches if necessary. Defaults to False. bool |
ent_id_sep | Separator used internally for entity IDs. Defaults to "||". str |
scorer | The scoring method. Defaults to spacy.scorer.get_ner_prf. Optional[Callable] |
explosion/spaCy/master/spacy/pipeline/entityruler.py
EntityRuler.__init__ method
Initialize the entity ruler. If patterns are supplied here, they need to be a
list of dictionaries with a "label" and "pattern" key. A pattern can either
be a token pattern (list) or a phrase pattern (string). For example:
{"label": "ORG", "pattern": "Apple"}.
| Name | Description |
|---|---|
nlp | The shared nlp object to pass the vocab to the matchers and process phrase patterns. Language |
name v3.0 | Instance name of the current pipeline component. Typically passed in automatically from the factory when the component is added. Used to disable the current entity ruler while creating phrase patterns with the nlp object. str |
| keyword-only | |
phrase_matcher_attr | Optional attribute name match on for the internal PhraseMatcher, e.g. LOWER to match on the lowercase token text. Defaults to None. Optional[Union[int, str]] |
matcher_fuzzy_compare v3.5 | The fuzzy comparison method, passed on to the internal Matcher. Defaults to spacy.matcher.levenshtein.levenshtein_compare. Callable |
validate | Whether patterns should be validated, passed to Matcher and PhraseMatcher as validate. Defaults to False. bool |
overwrite_ents | If existing entities are present, e.g. entities added by the model, overwrite them by matches if necessary. Defaults to False. bool |
ent_id_sep | Separator used internally for entity IDs. Defaults to "||". str |
patterns | Optional patterns to load in on initialization. Optional[List[Dict[str, Union[str, List[dict]]]]] |
scorer | The scoring method. Defaults to spacy.scorer.get_ner_prf. Optional[Callable] |
EntityRuler.initialize methodv3.0
Initialize the component with data and used before training to load in rules
from a pattern file. This
method is typically called by Language.initialize
and lets you customize arguments it receives via the
[initialize.components] block in the
config.
| Name | Description |
|---|---|
get_examples | Function that returns gold-standard annotations in the form of Example objects. Not used by the EntityRuler. Callable[[], Iterable[Example]] |
| keyword-only | |
nlp | The current nlp object. Defaults to None. Optional[Language] |
patterns | The list of patterns. Defaults to None. Optional[Sequence[Dict[str, Union[str, List[Dict[str, Any]]]]]] |
EntityRuler.__len__ method
The number of all patterns added to the entity ruler.
| Name | Description |
|---|---|
| RETURNS | The number of patterns. int |
EntityRuler.__contains__ method
Whether a label is present in the patterns.
| Name | Description |
|---|---|
label | The label to check. str |
| RETURNS | Whether the entity ruler contains the label. bool |
EntityRuler.__call__ method
Find matches in the Doc and add them to the doc.ents. Typically, this
happens automatically after the component has been added to the pipeline using
nlp.add_pipe. If the entity ruler was initialized
with overwrite_ents=True, existing entities will be replaced if they overlap
with the matches. When matches overlap in a Doc, the entity ruler prioritizes
longer patterns over shorter, and if equal the match occurring first in the Doc
is chosen.
| Name | Description |
|---|---|
doc | The Doc object to process, e.g. the Doc in the pipeline. Doc |
| RETURNS | The modified Doc with added entities, if available. Doc |
EntityRuler.add_patterns method
Add patterns to the entity ruler. A pattern can either be a token pattern (list of dicts) or a phrase pattern (string). For more details, see the usage guide on rule-based matching.
| Name | Description |
|---|---|
patterns | The patterns to add. List[Dict[str, Union[str, List[dict]]]] |
EntityRuler.remove methodv3.2.1
Remove a pattern by its ID from the entity ruler. A ValueError is raised if
the ID does not exist.
| Name | Description |
|---|---|
id | The ID of the pattern rule. str |
EntityRuler.to_disk method
Save the entity ruler patterns to a directory. The patterns will be saved as
newline-delimited JSON (JSONL). If a file with the suffix .jsonl is provided,
only the patterns are saved as JSONL. If a directory name is provided, a
patterns.jsonl and cfg file with the component configuration is exported.
| Name | Description |
|---|---|
path | A path to a JSONL file or directory, which will be created if it doesn’t exist. Paths may be either strings or Path-like objects. Union[str,Path] |
EntityRuler.from_disk method
Load the entity ruler from a path. Expects either a file containing
newline-delimited JSON (JSONL) with one entry per line, or a directory
containing a patterns.jsonl file and a cfg file with the component
configuration.
| Name | Description |
|---|---|
path | A path to a JSONL file or directory. Paths may be either strings or Path-like objects. Union[str,Path] |
| RETURNS | The modified EntityRuler object. EntityRuler |
EntityRuler.to_bytes method
Serialize the entity ruler patterns to a bytestring.
| Name | Description |
|---|---|
| RETURNS | The serialized patterns. bytes |
EntityRuler.from_bytes method
Load the pipe from a bytestring. Modifies the object in place and returns it.
| Name | Description |
|---|---|
bytes_data | The bytestring to load. bytes |
| RETURNS | The modified EntityRuler object. EntityRuler |
EntityRuler.labels property
All labels present in the match patterns.
| Name | Description |
|---|---|
| RETURNS | The string labels. Tuple[str, …] |
EntityRuler.ent_ids property
All entity IDs present in the id properties of the match patterns.
| Name | Description |
|---|---|
| RETURNS | The string IDs. Tuple[str, …] |
EntityRuler.patterns property
Get all patterns that were added to the entity ruler.
| Name | Description |
|---|---|
| RETURNS | The original patterns, one dictionary per pattern. List[Dict[str, Union[str, dict]]] |
Attributes
| Name | Description |
|---|---|
matcher | The underlying matcher used to process token patterns. Matcher |
phrase_matcher | The underlying phrase matcher used to process phrase patterns. PhraseMatcher |
token_patterns | The token patterns present in the entity ruler, keyed by label. Dict[str, List[Dict[str, Union[str, List[dict]]]] |
phrase_patterns | The phrase patterns present in the entity ruler, keyed by label. Dict[str, List[Doc]] |