Comments (3)
You can obtain the list of entities by calling entities()
method of the dictionary instance.
from wikipedia2vec import Wikipedia2Vec
model = Wikipedia2Vec.load(MODEL_FILE)
list(model.dictionary.entities())
from wikipedia2vec.
Okay, thanks a lot.
And is there any way to extract entities from a paragraph of text?
from wikipedia2vec.
Wikipedia2Vec does not currently provide a model to extract entities. You need to build a model based on the embeddings.
from wikipedia2vec.
Related Issues (20)
- progressively updating model with new text? HOT 1
- Embedding for <unknown> token. HOT 1
- How to add another tokenizer? HOT 3
- wiki2vec.get_entity_vector HOT 4
- Training on custom dataset HOT 2
- Wikipedia2Vec.load() KeyError HOT 4
- Fuzzy Matching HOT 1
- Throws binary incompatability error when importing on python 3.8 HOT 4
- Error for training with --case-sensitive True HOT 5
- UnicodeEncodeError: 'utf-8' codec can't encode characters in position 2-3: surrogates not allowed HOT 1
- Pip installation failed HOT 2
- Exploring the database - what type of database HOT 5
- Hello all i am getting this unicode error surrogate thing. i m a new user and have no idea what this is. i use this code everything month and never had this issue before. plz help!!! this is a client deliverable and i am stressing!!! HOT 2
- lmdb.Error: mdb_txn_commit: Input/output error when trying to train on dump file. HOT 3
- How to use build-mention-db output
- There was a problem loading the word vector binary file trained by myself
- BufferError after training embeddings HOT 2
- Wikipedia2Vec embedding training RAM requirements ?
- API? HOT 1
- Mapping with entities
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from wikipedia2vec.