`Found array with 0 sample(s)`

Lucy's team ran into this bug during the hackathon
>>> nlp("hydroxytryptophan")
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-231-7e41c1b0131c> in <module>
----> 1 nlp("hydroxytryptophan")

//anaconda/envs/scispacy/lib/python3.6/site-packages/spacy/language.py in __call__(self, text, disable, component_cfg)
    393             if not hasattr(proc, "__call__"):
    394                 raise ValueError(Errors.E003.format(component=type(proc), name=name))
--> 395             doc = proc(doc, **component_cfg.get(name, {}))
    396             if doc is None:
    397                 raise ValueError(Errors.E005.format(name=name))

//anaconda/envs/scispacy/lib/python3.6/site-packages/scispacy/umls_linking.py in __call__(self, doc)
     85 
     86         mention_strings = [x.text for x in mentions]
---> 87         batch_candidates = self.candidate_generator(mention_strings, self.k)
     88 
     89         for mention, candidates in zip(doc.ents, batch_candidates):

//anaconda/envs/scispacy/lib/python3.6/site-packages/scispacy/candidate_generation.py in __call__(self, mention_texts, k)
    201         if self.verbose:
    202             print(f'Generating candidates for {len(mention_texts)} mentions')
--> 203         tfidfs = self.vectorizer.transform(mention_texts)
    204         start_time = datetime.datetime.now()
    205 

//anaconda/envs/scispacy/lib/python3.6/site-packages/sklearn/feature_extraction/text.py in transform(self, raw_documents, copy)
   1679 
   1680         X = super().transform(raw_documents)
-> 1681         return self._tfidf.transform(X, copy=False)
   1682 
   1683     def _more_tags(self):

//anaconda/envs/scispacy/lib/python3.6/site-packages/sklearn/feature_extraction/text.py in transform(self, X, copy)
   1300         vectors : sparse matrix, [n_samples, n_features]
   1301         """
-> 1302         X = check_array(X, accept_sparse='csr', dtype=FLOAT_DTYPES, copy=copy)
   1303         if not sp.issparse(X):
   1304             X = sp.csr_matrix(X, dtype=np.float64)

//anaconda/envs/scispacy/lib/python3.6/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    548                              " minimum of %d is required%s."
    549                              % (n_samples, array.shape, ensure_min_samples,
--> 550                                 context))
    551 
    552     if ensure_min_features > 0 and array.ndim == 2:

ValueError: Found array with 0 sample(s) (shape=(0, 53479)) while a minimum of 1 is required.
allenai / scispacy

`Found array with 0 sample(s)` #144
