izuna385

import spacy
from spacy import displacy

doc2 = {
    "text": "But Google is starting from behind.",
    "ents": [{"start": 4, "end": 10, "label": "ORG"}],
    "title": None
}
displacy.render(doc2, style="ent", manual=True)

izuna385

class TypingPredictor:
    def __init__(self, typing_model, vocab, args):
        self.gpu = args.gpu
        self.model = typing_model
        self.cuda_device = args.cuda_device

        self.sequence_iterator = BasicIterator(batch_size=args.batch_size)
        self.sequence_iterator.index_with(vocab)

    def tonp(self,tsr):

izuna385

import spacy # version 2.1.4
import scispacy
nlp = spacy.load('en_core_sci_md')

def prevent_sentence_boundaries(doc):
    for i, token in enumerate(doc):
        if not can_be_sentence_start(token, doc):
            token.is_sent_start = False
    return doc

izuna385

dataset umls
dropout 0.5
train 1
bag_size 10
encoder position_cnn
struct_weight 0.5
typing_weight 0
multilabel_linking 0
parent_sample_size 100
bilinear_l2 0.0005