rename to KBEntryC

examples/pipeline/wikidata_entity_linking.py

@@ -61,23 +61,23 @@ def run_pipeline():
     to_create_kb = False
 
     # read KB back in from file
-    to_read_kb = False
+    to_read_kb = True
     to_test_kb = False
 
     # create training dataset
     create_wp_training = False
 
     # train the EL pipe
-    train_pipe = False
-    measure_performance = False
+    train_pipe = True
+    measure_performance = True
 
     # test the EL pipe on a simple example
-    to_test_pipeline = False
+    to_test_pipeline = True
 
     # write the NLP object, read back in and test again
-    to_write_nlp = False
+    to_write_nlp = True
     to_read_nlp = False
-    test_from_file = True
+    test_from_file = False
 
     # STEP 1 : create prior probabilities from WP (run only once)
     if to_create_prior_probs:
@@ -149,7 +149,7 @@ def run_pipeline():
         print("STEP 6: training Entity Linking pipe", datetime.datetime.now())
         # define the size (nr of entities) of training and dev set
         train_limit = 5000
-        dev_limit = 10000
+        dev_limit = 5000
 
         train_data = training_set_creator.read_training(nlp=nlp_2,
                                                         training_dir=TRAINING_DIR,
@@ -285,9 +285,7 @@ def _measure_accuracy(data, el_pipe=None):
 
     docs = [d for d, g in data if len(d) > 0]
     if el_pipe is not None:
-        print("applying el_pipe", datetime.datetime.now())
-        docs = list(el_pipe.pipe(docs, batch_size=10000000000))
-        print("done applying el_pipe", datetime.datetime.now())
+        docs = list(el_pipe.pipe(docs))
     golds = [g for d, g in data if len(d) > 0]
 
     for doc, gold in zip(docs, golds):

spacy/kb.pxd

@@ -9,8 +9,8 @@ from libc.stdio cimport FILE
 from spacy.vocab cimport Vocab
 from .typedefs cimport hash_t
 
-from .structs cimport EntryC, AliasC
-ctypedef vector[EntryC] entry_vec
+from .structs cimport KBEntryC, AliasC
+ctypedef vector[KBEntryC] entry_vec
 ctypedef vector[AliasC] alias_vec
 ctypedef vector[float] float_vec
 ctypedef vector[float_vec] float_matrix
@@ -32,7 +32,7 @@ cdef class KnowledgeBase:
     cdef int64_t entity_vector_length
 
     # This maps 64bit keys (hash of unique entity string)
-    # to 64bit values (position of the _EntryC struct in the _entries vector).
+    # to 64bit values (position of the _KBEntryC struct in the _entries vector).
     # The PreshMap is pretty space efficient, as it uses open addressing. So
     # the only overhead is the vacancy rate, which is approximately 30%.
     cdef PreshMap _entry_index
@@ -88,7 +88,7 @@ cdef class KnowledgeBase:
         cdef int64_t new_index = self._entries.size()
 
         # Avoid struct initializer to enable nogil, cf https://github.com/cython/cython/issues/1642
-        cdef EntryC entry
+        cdef KBEntryC entry
         entry.entity_hash = entity_hash
         entry.vector_index = vector_index
         entry.feats_row = feats_row
@@ -121,7 +121,7 @@ cdef class KnowledgeBase:
         cdef int32_t dummy_value = 0
 
         # Avoid struct initializer to enable nogil
-        cdef EntryC entry
+        cdef KBEntryC entry
         entry.entity_hash = dummy_hash
         entry.vector_index = dummy_value
         entry.feats_row = dummy_value

spacy/kb.pyx

@@ -129,7 +129,7 @@ cdef class KnowledgeBase:
         self._entries = entry_vec(nr_entities+1)
 
         i = 0
-        cdef EntryC entry
+        cdef KBEntryC entry
         while i < nr_entities:
             entity_vector = vector_list[i]
             if len(entity_vector) != self.entity_vector_length:
@@ -250,7 +250,7 @@ cdef class KnowledgeBase:
         cdef int64_t entry_index
         cdef float prob
         cdef int32_t vector_index
-        cdef EntryC entry
+        cdef KBEntryC entry
         cdef AliasC alias
         cdef float vector_element
 

spacy/structs.pxd

@@ -79,7 +79,7 @@ cdef struct TokenC:
 
 
 # Internal struct, for storage and disambiguation of entities.
-cdef struct EntryC:
+cdef struct KBEntryC:
 
     # The hash of this entry's unique ID/name in the kB
     hash_t entity_hash