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Remove references to textcat spans (#5360)

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Remove references to unimplemented `TextCategorizer` span labels in
`GoldParse` and `Doc`.
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adrianeboyd 2020-04-27 18:01:12 +02:00 committed by GitHub
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website/docs/api/doc.md
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@ -653,7 +653,7 @@ The L2 norm of the document's vector representation.
| `mem` | `Pool` | The document's local memory heap, for all C data it owns. |
| `vocab` | `Vocab` | The store of lexical types. |
| `tensor` <Tag variant="new">2</Tag> | `ndarray` | Container for dense vector representations. |
| `cats` <Tag variant="new">2</Tag> | dictionary | Maps either a label to a score for categories applied to whole document, or `(start_char, end_char, label)` to score for categories applied to spans. `start_char` and `end_char` should be character offsets, label can be either a string or an integer ID, and score should be a float. |
| `cats` <Tag variant="new">2</Tag> | dict | Maps a label to a score for categories applied to the document. The label is a string and the score should be a float. |
| `user_data` | - | A generic storage area, for user custom data. |
| `lang` <Tag variant="new">2.1</Tag> | int | Language of the document's vocabulary. |
| `lang_` <Tag variant="new">2.1</Tag> | unicode | Language of the document's vocabulary. |

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website/docs/api/goldparse.md
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@ -7,12 +7,10 @@ source: spacy/gold.pyx
## GoldParse.\_\_init\_\_ {#init tag="method"}
Create a `GoldParse`. Unlike annotations in `entities`, label annotations in
`cats` can overlap, i.e. a single word can be covered by multiple labelled
spans. The [`TextCategorizer`](/api/textcategorizer) component expects true
examples of a label to have the value `1.0`, and negative examples of a label to
have the value `0.0`. Labels not in the dictionary are treated as missing – the
gradient for those labels will be zero.
Create a `GoldParse`. The [`TextCategorizer`](/api/textcategorizer) component
expects true examples of a label to have the value `1.0`, and negative examples
of a label to have the value `0.0`. Labels not in the dictionary are treated as
missing – the gradient for those labels will be zero.
| Name | Type | Description |
| ----------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
@ -22,8 +20,8 @@ gradient for those labels will be zero.
| `heads` | iterable | A sequence of integers, representing syntactic head offsets. |
| `deps` | iterable | A sequence of strings, representing the syntactic relation types. |
| `entities` | iterable | A sequence of named entity annotations, either as BILUO tag strings, or as `(start_char, end_char, label)` tuples, representing the entity positions. If BILUO tag strings, you can specify missing values by setting the tag to None. |
| `cats` | dict | Labels for text classification. Each key in the dictionary may be a string or an int, or a `(start_char, end_char, label)` tuple, indicating that the label is applied to only part of the document (usually a sentence). |
| `links` | dict | Labels for entity linking. A dict with `(start_char, end_char)` keys, and the values being dicts with `kb_id:value` entries, representing external KB IDs mapped to either 1.0 (positive) or 0.0 (negative). |
| `cats` | dict | Labels for text classification. Each key in the dictionary is a string label for the category and each value is `1.0` (positive) or `0.0` (negative). |
| `links` | dict | Labels for entity linking. A dict with `(start_char, end_char)` keys, and the values being dicts with `kb_id:value` entries, representing external KB IDs mapped to either `1.0` (positive) or `0.0` (negative). |
| **RETURNS** | `GoldParse` | The newly constructed object. |
## GoldParse.\_\_len\_\_ {#len tag="method"}
@ -53,7 +51,7 @@ Whether the provided syntactic annotations form a projective dependency tree.
| `ner` | list | The named entity annotations as BILUO tags. |
| `cand_to_gold` | list | The alignment from candidate tokenization to gold tokenization. |
| `gold_to_cand` | list | The alignment from gold tokenization to candidate tokenization. |
| `cats` <Tag variant="new">2</Tag> | list | Entries in the list should be either a label, or a `(start, end, label)` triple. The tuple form is used for categories applied to spans of the document. |
| `cats` <Tag variant="new">2</Tag> | dict | Keys in the dictionary are string category labels with values `1.0` or `0.0`. |
| `links` <Tag variant="new">2.2</Tag> | dict | Keys in the dictionary are `(start_char, end_char)` triples, and the values are dictionaries with `kb_id:value` entries. |
## Utilities {#util}