Rooba
/
spaCy
mirror of https://github.com/explosion/spaCy.git
1
1
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Fix typos in docs (#13466) 

* fix typos

* prettier formatting

---------

Co-authored-by: svlandeg <svlandeg@github.com>
This commit is contained in:
Alex Strick van Linschoten 2024-04-29 11:10:17 +02:00 committed by GitHub
parent 74836524e3
commit 045cd43c3f
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
14 changed files with 69 additions and 66 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
spacy/cli/find_threshold.py
View File

@ -39,7 +39,7 @@ def find_threshold_cli(
# fmt: on
):
"""
Runs prediction trials for a trained model with varying tresholds to maximize
Runs prediction trials for a trained model with varying thresholds to maximize
the specified metric. The search space for the threshold is traversed linearly
from 0 to 1 in `n_trials` steps. Results are displayed in a table on `stdout`
(the corresponding API call to `spacy.cli.find_threshold.find_threshold()`
@ -81,7 +81,7 @@ def find_threshold(
silent: bool = True,
) -> Tuple[float, float, Dict[float, float]]:
"""
Runs prediction trials for models with varying tresholds to maximize the specified metric.
Runs prediction trials for models with varying thresholds to maximize the specified metric.
model (Union[str, Path]): Pipeline to evaluate. Can be a package or a path to a data directory.
data_path (Path): Path to file with DocBin with docs to use for threshold search.
pipe_name (str): Name of pipe to examine thresholds for.

2
spacy/tests/test_language.py
View File

@ -329,7 +329,7 @@ def test_language_pipe_error_handler(n_process):
nlp.set_error_handler(raise_error)
with pytest.raises(ValueError):
list(nlp.pipe(texts, n_process=n_process))
# set explicitely to ignoring
# set explicitly to ignoring
nlp.set_error_handler(ignore_error)
docs = list(nlp.pipe(texts, n_process=n_process))
assert len(docs) == 0

4
website/docs/api/attributes.mdx
View File

@ -46,10 +46,10 @@ as `Token.attr`, e.g. `token.dep`, while the string value can be retrieved by
appending `_` as in `token.dep_`.
| Attribute | Description |
| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `DEP` | The token's dependency label. ~~str~~ |
| `ENT_ID` | The token's entity ID (`ent_id`). ~~str~~ |
| `ENT_IOB` | The IOB part of the token's entity tag. Uses custom integer vaues rather than the string store: unset is `0`, `I` is `1`, `O` is `2`, and `B` is `3`. ~~str~~ |
| `ENT_IOB` | The IOB part of the token's entity tag. Uses custom integer values rather than the string store: unset is `0`, `I` is `1`, `O` is `2`, and `B` is `3`. ~~str~~ |
| `ENT_KB_ID` | The token's entity knowledge base ID. ~~str~~ |
| `ENT_TYPE` | The token's entity label. ~~str~~ |
| `IS_ALPHA` | Token text consists of alphabetic characters. ~~bool~~ |

4
website/docs/api/cli.mdx
View File

@ -567,7 +567,7 @@ New: 'ORG' (23860), 'PERSON' (21395), 'GPE' (21193), 'DATE' (18080), 'CARDINAL'
'LOC' (2113), 'TIME' (1616), 'WORK_OF_ART' (1229), 'QUANTITY' (1150), 'FAC'
(1134), 'EVENT' (974), 'PRODUCT' (935), 'LAW' (444), 'LANGUAGE' (338)
✔ Good amount of examples for all labels
✔ Examples without occurences available for all labels
✔ Examples without occurrences available for all labels
✔ No entities consisting of or starting/ending with whitespace
=========================== Part-of-speech Tagging ===========================
@ -1320,7 +1320,7 @@ $ python -m spacy apply [model] [data-path] [output-file] [--code] [--text-key]
## find-threshold {id="find-threshold",version="3.5",tag="command"}
Runs prediction trials for a trained model with varying tresholds to maximize
Runs prediction trials for a trained model with varying thresholds to maximize
the specified metric. The search space for the threshold is traversed linearly
from 0 to 1 in `n_trials` steps. Results are displayed in a table on `stdout`
(the corresponding API call to `spacy.cli.find_threshold.find_threshold()`

6
website/docs/api/entitylinker.mdx
View File

@ -67,7 +67,7 @@ architectures and their arguments and hyperparameters.
| `generate_empty_kb` <Tag variant="new">3.5.1</Tag> | Function that generates an empty `KnowledgeBase` object. Defaults to [`spacy.EmptyKB.v2`](/api/architectures#EmptyKB), which generates an empty [`InMemoryLookupKB`](/api/inmemorylookupkb). ~~Callable[[Vocab, int], KnowledgeBase]~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the threshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
```python
%%GITHUB_SPACY/spacy/pipeline/entity_linker.py
@ -101,7 +101,7 @@ custom knowledge base, you should either call
[`initialize`](/api/entitylinker#initialize) call.
| Name | Description |
| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vocab` | The shared vocabulary. ~~Vocab~~ |
| `model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~ |
| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
@ -114,7 +114,7 @@ custom knowledge base, you should either call
| `incl_context` | Whether or not to include the local context in the model. ~~bool~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the threshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
## EntityLinker.\_\_call\_\_ {id="call",tag="method"}

2
website/docs/api/entityruler.mdx
View File

@ -173,7 +173,7 @@ happens automatically after the component has been added to the pipeline using
[`nlp.add_pipe`](/api/language#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 occuring first in the Doc
longer patterns over shorter, and if equal the match occurring first in the Doc
is chosen.
> #### Example

2
website/docs/api/span.mdx
View File

@ -288,7 +288,7 @@ it – so no NP-level coordination, no prepositional phrases, and no relative
clauses.
If the `noun_chunk` [syntax iterator](/usage/linguistic-features#language-data)
has not been implemeted for the given language, a `NotImplementedError` is
has not been implemented for the given language, a `NotImplementedError` is
raised.
> #### Example

2
website/docs/api/transformer.mdx
View File

@ -416,7 +416,7 @@ by this class. Instances of this class are typically assigned to the
| `align` | Alignment from the `Doc`'s tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
| `width` | The width of the last hidden layer. ~~int~~ |
### TransformerData.empty {id="transformerdata-emoty",tag="classmethod"}
### TransformerData.empty {id="transformerdata-empty",tag="classmethod"}
Create an empty `TransformerData` container.

2
website/docs/usage/layers-architectures.mdx
View File

@ -832,7 +832,7 @@ retrieve and add to them.
After creation, the component needs to be
[initialized](/usage/training#initialization). This method can define the
relevant labels in two ways: explicitely by setting the `labels` argument in the
relevant labels in two ways: explicitly by setting the `labels` argument in the
[`initialize` block](/api/data-formats#config-initialize) of the config, or
implicately by deducing them from the `get_examples` callback that generates the
full **training data set**, or a representative sample.

2
website/docs/usage/linguistic-features.mdx
View File

@ -1899,7 +1899,7 @@ the two words.
"Shore": ("coast", 0.732257),
"Precautionary": ("caution", 0.490973),
"hopelessness": ("sadness", 0.742366),
"Continous": ("continuous", 0.732549),
"Continuous": ("continuous", 0.732549),
"Disemboweled": ("corpse", 0.499432),
"biostatistician": ("scientist", 0.339724),
"somewheres": ("somewheres", 0.402736),

4
website/docs/usage/projects.mdx
View File

@ -173,7 +173,7 @@ detected, a corresponding warning is displayed. If you'd like to disable the
dependency check, set `check_requirements: false` in your project's
`project.yml`.
### 4. Run a workflow {id="run-workfow"}
### 4. Run a workflow {id="run-workflow"}
> #### project.yml
>
@ -286,7 +286,7 @@ pipelines.
| --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `title` | An optional project title used in `--help` message and [auto-generated docs](#custom-docs). |
| `description` | An optional project description used in [auto-generated docs](#custom-docs). |
| `vars` | A dictionary of variables that can be referenced in paths, URLs and scripts and overriden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`. |
| `vars` | A dictionary of variables that can be referenced in paths, URLs and scripts and overridden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`. |
| `env` | A dictionary of variables, mapped to the names of environment variables that will be read in when running the project. For example, `${env.name}` will use the value of the environment variable defined as `name`. |
| `directories` | An optional list of [directories](#project-files) that should be created in the project for assets, training outputs, metrics etc. spaCy will make sure that these directories always exist. |
| `assets` | A list of assets that can be fetched with the [`project assets`](/api/cli#project-assets) command. `url` defines a URL or local path, `dest` is the destination file relative to the project directory, and an optional `checksum` ensures that an error is raised if the file's checksum doesn't match. Instead of `url`, you can also provide a `git` block with the keys `repo`, `branch` and `path`, to download from a Git repo. |

11
website/docs/usage/saving-loading.mdx
View File

@ -306,7 +306,9 @@ installed in the same environment – that's it.
### Loading probability tables into existing models
You can load a probability table from [spacy-lookups-data](https://github.com/explosion/spacy-lookups-data) into an existing spaCy model like `en_core_web_sm`.
You can load a probability table from
[spacy-lookups-data](https://github.com/explosion/spacy-lookups-data) into an
existing spaCy model like `en_core_web_sm`.
```python
# Requirements: pip install spacy-lookups-data
@ -317,7 +319,8 @@ lookups = load_lookups("en", ["lexeme_prob"])
nlp.vocab.lookups.add_table("lexeme_prob", lookups.get_table("lexeme_prob"))
```
When training a model from scratch you can also specify probability tables in the `config.cfg`.
When training a model from scratch you can also specify probability tables in
the `config.cfg`.
```ini {title="config.cfg (excerpt)"}
[initialize.lookups]
@ -346,8 +349,8 @@ them**!
To stick with the theme of
[this entry points blog post](https://amir.rachum.com/blog/2017/07/28/python-entry-points/),
consider the following custom spaCy
[pipeline component](/usage/processing-pipelines#custom-coponents) that prints a
snake when it's called:
[pipeline component](/usage/processing-pipelines#custom-components) that prints
a snake when it's called:
> #### Package directory structure
>

2
website/docs/usage/v2-2.mdx
View File

@ -185,7 +185,7 @@ New: 'ORG' (23860), 'PERSON' (21395), 'GPE' (21193), 'DATE' (18080), 'CARDINAL'
'LOC' (2113), 'TIME' (1616), 'WORK_OF_ART' (1229), 'QUANTITY' (1150), 'FAC'
(1134), 'EVENT' (974), 'PRODUCT' (935), 'LAW' (444), 'LANGUAGE' (338)
✔ Good amount of examples for all labels
✔ Examples without occurences available for all labels
✔ Examples without occurrences available for all labels
✔ No entities consisting of or starting/ending with whitespace
=========================== Part-of-speech Tagging ===========================

2
website/docs/usage/v3-2.mdx
View File

@ -138,7 +138,7 @@ backwards compatibility, the tuple format remains available under
`TransformerData.tensors` and `FullTransformerBatch.tensors`. See more details
in the [transformer API docs](/api/architectures#TransformerModel).
`spacy-transfomers` v1.1 also adds support for `transformer_config` settings
`spacy-transformers` v1.1 also adds support for `transformer_config` settings
such as `output_attentions`. Additional output is stored under
`TransformerData.model_output`. More details are in the
[TransformerModel docs](/api/architectures#TransformerModel). The training speed