* Limiting noun_chunks for specific langauges
* Limiting noun_chunks for specific languages
Contributor Agreement
* Addressing review comments
* Removed unused fixtures and imports
* Add fa_tokenizer in test suite
* Use fa_tokenizer in test
* Undo extraneous reformatting
Co-authored-by: adrianeboyd <adrianeboyd@gmail.com>
Check that row is within bounds for the vector data array when adding a
vector.
Don't add vectors with rank OOV_RANK in `init-model` (change is due to
shift from OOV as 0 to OOV as OOV_RANK).
Remove `TAG` value from Danish and Swedish tokenizer exceptions because
it may not be included in a tag map (and these settings are problematic
as tokenizer exceptions anyway).
Instead of treating `'d` in contractions like `I'd` as `would` in all
cases in the tokenizer exceptions, leave the tagging and lemmatization
up to later components.
* Initialize lower flag explicitly
* Handle whitespace words from GoldParse correctly when creating raw
text with orth variants
* Return the text with original casing if anything goes wrong
* `debug-data`: determine coverage of provided vectors
* `evaluate`: support `blank:lg` model to make it possible to just evaluate
tokenization
* `init-model`: add option to truncate vectors to N most frequent vectors
from word2vec file
* `train`:
* if training on GPU, only run evaluation/timing on CPU in the first
iteration
* if training is aborted, exit with a non-0 exit status
* simplify creation of KB by skipping dim reduction
* small fixes to train EL example script
* add KB creation and NEL training example scripts to example section
* update descriptions of example scripts in the documentation
* moving wiki_entity_linking folder from bin to projects
* remove test for wiki NEL functionality that is being moved
Reconstruction of the original PR #4697 by @MiniLau.
Removes unused `SENT_END` symbol and `IS_SENT_END` from `Matcher` schema
because the Matcher is only going to be able to support `IS_SENT_START`.
Improve GoldParse NER alignment by including all cases where the start
and end of the NER span can be aligned, regardless of internal
tokenization differences.
To do this, convert BILUO tags to character offsets, check start/end
alignment with `doc.char_span()`, and assign the BILUO tags for the
aligned spans. Alignment for `O/-` tags is handled through the
one-to-one and multi alignments.
* The embedding vis. link is broken
The first link seems to be reasonable for now unless someone has an updated embedding vis they want to share?
* contributor agreement
* Update Mlawrence95.md
* Update website/docs/usage/examples.md
Co-Authored-By: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Modify jieba install message to instruct the user to use
`ChineseDefaults.use_jieba = False` so that it's possible to load
pkuseg-only models without jieba installed.
