explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-11-04 01:48:04 +03:00
Code Issues Packages Projects Releases Wiki Activity

Update 101 and usage docs

Browse Source
This commit is contained in:
ines 2017-05-28 00:03:16 +02:00
parent 49235017bf
commit b03fb2d7b0
4 changed files with 7 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
website/docs/usage/_spacy-101/_vocab-stringstore.jade
View File

@ -89,4 +89,6 @@ p
p p
| Even though both #[code Doc] objects contain the same words, the internal | Even though both #[code Doc] objects contain the same words, the internal
| integer IDs are very different. | integer IDs are very different. The same applies for all other strings,
| like the annotation scheme. To avoid mismatched IDs, spaCy will always
| export the vocab if you save a #[code Doc] or #[code nlp] object.

2
website/docs/usage/lightning-tour.jade
View File

@ -139,6 +139,8 @@ p
new_doc = Doc(Vocab()).from_disk('/moby_dick.bin') new_doc = Doc(Vocab()).from_disk('/moby_dick.bin')
+infobox +infobox
| #[strong API:] #[+api("language") #[code Language]],
| #[+api("doc") #[code Doc]]
| #[strong Usage:] #[+a("/docs/usage/saving-loading") Saving and loading] | #[strong Usage:] #[+a("/docs/usage/saving-loading") Saving and loading]
+h(2, "rule-matcher") Match text with token rules +h(2, "rule-matcher") Match text with token rules

2
website/docs/usage/rule-based-matching.jade
View File

@ -345,7 +345,7 @@ p
| account and check the #[code subtree] for intensifiers like "very", to | account and check the #[code subtree] for intensifiers like "very", to
| increase the sentiment score. At some point, you might also want to train | increase the sentiment score. At some point, you might also want to train
| a sentiment model. However, the approach described in this example is | a sentiment model. However, the approach described in this example is
| very useful for #[strong bootstrapping rules to gather training data]. | very useful for #[strong bootstrapping rules to collect training data].
| It's also an incredibly fast way to gather first insights into your data | It's also an incredibly fast way to gather first insights into your data
| – with about 1 million tweets, you'd be looking at a processing time of | – with about 1 million tweets, you'd be looking at a processing time of
| #[strong under 1 minute]. | #[strong under 1 minute].