A couple of fixes on write_xml in create_xml.py + Created form_csv.py script

scripts/create_xml.py

@@ -3,6 +3,7 @@
 
 #imports from luscenje_struktur
 import copy
+import csv
 
 from luscenje_struktur.progress_bar import progress
 from luscenje_struktur.word import Word, WordCompressed
@@ -114,6 +115,8 @@ CASE_MAP = {
     'i': 'instrumental'
 }
 
+ssj_frequency_dict = {}
+
 
 Lexeme = None
 LexemeFeature = None
@@ -130,6 +133,7 @@ Definition = None
 WordForm = None
 WordFormFeature = None
 FormRepresentation = None
+FormEncoding = None
 
 
 # corpus = 'gigafida'
@@ -745,7 +749,7 @@ def obtain_xml_data(collection, w_a_collection, headword_text, RF, mongo, patter
 
 def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo, session, w_a_collection_ssj, w_a_collection_gigafida, valency_pattern_id_collection, corpus_name, pattern_examples_limit, ignore_gigafida, pbar):
     query_general = session.query(Lexeme.id, LexicalUnitLexeme.id, LexicalUnit.id, LexicalUnitMeasure.value,
-                                  Lexeme.dummy, LexicalUnitType.name) \
+                                  Lexeme.potential_lexeme, LexicalUnitType.name) \
         .join(Category, Category.id == Lexeme.category_id) \
         .join(LexicalUnitLexeme, LexicalUnitLexeme.lexeme_id == Lexeme.id) \
         .join(LexicalUnit, LexicalUnit.id == LexicalUnitLexeme.lexical_unit_id) \
@@ -791,7 +795,8 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
         wf1 = aliased(WordFormFeature)
         wf2 = aliased(WordFormFeature)
         wf3 = aliased(WordFormFeature)
-        query_preposition = session.query(FormRepresentation.form) \
+        query_preposition = session.query(FormEncoding.text) \
+            .join(FormRepresentation, FormRepresentation.id == FormEncoding.form_representation_id) \
             .join(WordForm, WordForm.id == FormRepresentation.word_form_id) \
             .join(Lexeme, Lexeme.id == WordForm.lexeme_id) \
             .join(wf1, wf1.word_form_id == WordForm.id) \
@@ -805,7 +810,7 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
 
         pattern_translation_3_sin = headword_text
         if len(pattern_translation_hws) == 1:
-            pattern_translation_3_sin = pattern_translation_hws[0].form
+            pattern_translation_3_sin = pattern_translation_hws[0].text
 
         qname = etree.QName("http://www.w3.org/2001/XMLSchema-instance", "noNamespaceSchemaLocation")
         dictionary = lxml.Element('dictionary', {qname: 'valency_lexicon.xsd'})
@@ -816,6 +821,7 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
             headword_text_query = headword_text[:-1]
         else:
             headword_text_query = headword_text
+
         query = query_general.filter(Category.name == category_text) \
             .filter(Lexeme.lemma == headword_text_query) \
             .group_by(Lexeme.id, LexicalUnitLexeme.id, LexicalUnit.id, LexicalUnitMeasure.value,
@@ -827,31 +833,91 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
         if len(query_res) == 1:
             (lexeme_id, lexical_unit_lexeme_id, lexical_unit_id, frequency, _, lexical_unit_type_name) = \
             query_res[0]
+            sense_ids = session.query(Sense.id, Sense.potential_sense).filter(
+                Sense.lexical_unit_id == lexical_unit_id).all()
+            features = session.query(LexemeFeature.value).join(Feature, Feature.id == LexemeFeature.feature_id) \
+                .filter(LexemeFeature.lexeme_id == lexeme_id) \
+                .filter(Feature.name == 'aspect').all()
 
         elif len(query_res) > 1:
+            # find dummy
+            dummy_query = session.query(Lexeme.id, LexicalUnitLexeme.id, LexicalUnit.id,
+                               Lexeme.potential_lexeme, LexicalUnitType.name) \
+                .join(Category, Category.id == Lexeme.category_id) \
+                .join(LexicalUnitLexeme, LexicalUnitLexeme.lexeme_id == Lexeme.id) \
+                .join(LexicalUnit, LexicalUnit.id == LexicalUnitLexeme.lexical_unit_id) \
+                .join(LexicalUnitType, LexicalUnitType.id == LexicalUnit.type_id) \
+                .filter(LexicalUnitType.name == 'single_lexeme_unit') \
+                .filter(Corpus.name == 'gigafida') \
+                .filter(Corpus.version == '2.0') \
+                .filter(Lexeme.lemma == headword_text_query).all()
+
             # all lexical_unit_ids equal or at least one dummy
+            dummy_exists = False
             final_lexical_unit_id = 0
             final_lexical_unit_lexeme_id = 0
-            for r in query_res:
+            for r in dummy_query:
-                (lexeme_id, lexical_unit_lexeme_id, lexical_unit_id, frequency, dummy,
+                (lexeme_id, lexical_unit_lexeme_id, lexical_unit_id, dummy,
                  lexical_unit_type_name) = r
                 if dummy:
                     final_lexical_unit_id = lexical_unit_id
                     final_lexical_unit_lexeme_id = lexical_unit_lexeme_id
+                    dummy_exists = True
                     break
+            assert dummy_exists
+
+            sense_ids = []
+            features_set = set()
+            frequency = 0
+            for r in query_res:
+                (lexeme_id, lexical_unit_lexeme_id, lexical_unit_id, el_frequency, dummy,
+                 lexical_unit_type_name) = r
+                if dummy:
+                    continue
+                sense_ids.extend(session.query(Sense.id, Sense.potential_sense).filter(
+                    Sense.lexical_unit_id == lexical_unit_id).all())
+                features = session.query(LexemeFeature.value).join(Feature, Feature.id == LexemeFeature.feature_id) \
+                    .filter(LexemeFeature.lexeme_id == lexeme_id) \
+                    .filter(Feature.name == 'aspect').all()
+
+                # set features in dictionary
+                if not features:
+                    for n_feat in features_set:
+                        for f in n_feat:
+                            features.add(f)
+                # compare features
+                else:
+                    for n_feat in features_set:
+                        for f in n_feat:
+                            if f not in features:
+                                raise Exception('Different features in query_res - might be problematic!')
+
+
+
+                frequency += el_frequency
+
+            # check if any actual sense exists if not erase all but one
+            any_sense_not_dummy = any([not sense[1] for sense in sense_ids])
+            if not any_sense_not_dummy:
+                sense_ids = sense_ids[-1:]
+
+
             lexical_unit_id = final_lexical_unit_id
             lexical_unit_lexeme_id = final_lexical_unit_lexeme_id
+            # sense_ids = session.query(Sense.id, Sense.potential_sense).filter(
+            #     Sense.lexical_unit_id == lexical_unit_id).all()
+            # features = session.query(LexemeFeature.value).join(Feature, Feature.id == LexemeFeature.feature_id) \
+            #     .filter(LexemeFeature.lexeme_id == lexeme_id) \
+            #     .filter(Feature.name == 'aspect').all()
         else:
-            frequency = 0
+            frequency = None
             lexeme_id = 0
             lexical_unit_id = 0
             lexical_unit_lexeme_id = 0
             lexical_unit_type_name = ''
+            sense_ids = []
+            features = []
 
-        sense_ids = session.query(Sense.id, Sense.dummy).filter(Sense.lexical_unit_id == lexical_unit_id).all()
-        features = session.query(LexemeFeature.value).join(Feature, Feature.id == LexemeFeature.feature_id) \
-            .filter(LexemeFeature.lexeme_id == lexeme_id) \
-            .filter(Feature.name == 'aspect').all()
 
         entry = lxml.SubElement(dictionary, 'entry')
 
@@ -875,23 +941,33 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
             category.text = CATEGORY_MAP[category_text] if category_text in CATEGORY_MAP else ''
         else:
             category.text = category_text
+        ssj_frequency = None
+        if len(features) > 0:
             grammarFeature = lxml.SubElement(grammar, 'grammarFeature')
+            ssj_frequency = ssj_frequency_dict[(headword_text, features[0].value)] if (headword_text, features[0].value) in ssj_frequency_dict else None
             if args.language == 'sl':
                 grammarFeature.set('name', 'vid')
-            grammarFeature.text = ASPECT_MAP[features[0].value] if len(features) > 0 and features[
+                if len(features) > 1:
-                0].value in ASPECT_MAP else ''
+                    print(features)
+                grammarFeature.text = ASPECT_MAP[features[0].value]
             else:
                 grammarFeature.set('name', 'aspect')
-            grammarFeature.text = features[0].value if len(features) > 0 else ''
+                grammarFeature.text = features[0].value
 
         measureList = lxml.SubElement(head, 'measureList')
+        if frequency:
             measure = lxml.SubElement(measureList, 'measure')
             measure.set('type', 'frequency')
-        # TODO Modify this!
             measure.set('source', 'Gigafida 2.0')
             # measure.set('source', 'ssj500k')
             measure.text = str(int(frequency))
 
+            if ssj_frequency is not None:
+                measure = lxml.SubElement(measureList, 'measure')
+                measure.set('type', 'frequency')
+                measure.set('source', 'ssj500k 2.2')
+                measure.text = str(int(ssj_frequency))
+
 
 
 
@@ -956,18 +1032,26 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
                                 semantic_role_stats[semanticRole_val]['gf']['valency_sentence_num'] / sentence_tot_gf)
 
         senseList = lxml.SubElement(body, 'senseList')
+
+        # handle cases when headword is not in sloleks
+        if len(sense_ids) == 0:
+            sense_ids = [-1]
+
         for sense_id in sense_ids:
-            if len(sense_ids) > 1 and sense_id.dummy:
+            if len(sense_ids) > 1 and sense_id.potential_sense:
                 continue
 
             sense = lxml.SubElement(senseList, 'sense')
-            if not sense_id.dummy:
+            if not sense_id == -1 and not sense_id.potential_sense:
                 sense.set('id', str(sense_id.id))
 
             definitionList = lxml.SubElement(sense, 'definitionList')
 
+            if not sense_id == -1:
                 definition_texts = session.query(Definition.description).filter(
                     Definition.sense_id == sense_id.id).all()
+            else:
+                definition_texts = []
 
             for definition_text in definition_texts:
                 definition = lxml.SubElement(definitionList, 'definition')
@@ -1050,11 +1134,9 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
                         for syn_struct_id, component_dict in syntactic_structure_dict.items():
                             syntacticStructure = lxml.SubElement(syntacticStructureList, 'syntacticStructure')
                             syntacticStructure.set('id', syn_struct_id)
+                            dedup_dict = {}
                             for comp_id, lexemes in component_dict.items():
                                 for l in lexemes:
-                                    component = lxml.SubElement(syntacticStructure, 'component')
-                                    component.set('num', comp_id)
-                                    lexem = lxml.SubElement(component, 'lexeme')
 
                                     if l in preposition_list:
                                         prep_id = preposition_list[l]
@@ -1074,6 +1156,13 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
                                             prep_id = str(preposition_ids[0][0])
                                         preposition_list[l] = prep_id
 
+                                    if comp_id in dedup_dict and prep_id in dedup_dict[comp_id] and l[2] in dedup_dict[comp_id][prep_id]:
+                                        continue
+
+                                    dedup_dict.setdefault(comp_id, {})[prep_id] = l[2]
+                                    component = lxml.SubElement(syntacticStructure, 'component')
+                                    component.set('num', comp_id)
+                                    lexem = lxml.SubElement(component, 'lexeme')
 
                                     lexem.set('sloleks', prep_id)
                                     lexem.text = l[2]
@@ -1100,7 +1189,7 @@ def write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo,
 
 
 def init_db(db):
-    global Lexeme, LexemeFeature, Feature, LexicalUnitLexeme, LexicalUnit, LexicalUnitType, Category, Sense, Measure, LexicalUnitMeasure, Corpus, Definition, WordForm, WordFormFeature, FormRepresentation
+    global Lexeme, LexemeFeature, Feature, LexicalUnitLexeme, LexicalUnit, LexicalUnitType, Category, Sense, Measure, LexicalUnitMeasure, Corpus, Definition, WordForm, WordFormFeature, FormRepresentation, FormEncoding
     [db_user, db_password, db_database, db_host] = db.split(':')
     Base = declarative_base()
     engine = create_engine('postgresql://' + db_user + ':' + db_password + '@' + db_host + '/' + db_database,
@@ -1152,6 +1241,9 @@ def init_db(db):
     class FormRepresentation(Base):
         __table__ = Base.metadata.tables['jedro_formrepresentation']
 
+    class FormEncoding(Base):
+        __table__ = Base.metadata.tables['jedro_formencoding']
+
     return engine
 
 
@@ -1415,6 +1507,14 @@ def get_headword_category(collection):
     return headword_category
 
 
+def read_ssj500k_frequencies(path):
+    with open(path, 'r') as f:
+        reader = csv.reader(f, delimiter='\t')
+        next(reader)
+        for line in reader:
+            ssj_frequency_dict[(line[1], line[-1])] = line[2]
+
+
 def main(args):
     # with Path('data/wordlist.json').open("r") as fp:
     #     sskj_wordlist = json.load(fp)
@@ -1518,7 +1618,9 @@ def main(args):
 
     print('write_xml')
     start_time = time.time()
-    # print('aa ' + 3)
+    if args.ssj500k_frequencies is not None:
+        read_ssj500k_frequencies(args.ssj500k_frequencies)
+
     with tqdm(total=len(headword_category)) as pbar:
         write_xml(headword_category, collection_ssj, collection_gigafida, RF, mongo, session, w_a_collection_ssj, w_a_collection_gigafida, valency_pattern_id_collection, args.corpus_name, args.pattern_examples_limit, args.ignore_gigafida, pbar)
     print(time.time() - start_time)
@@ -1592,6 +1694,9 @@ if __name__ == '__main__':
     arg_parser.add_argument('--pc-tag',
                         help='Tag for separators, usually pc or c', default="pc")
 
+    arg_parser.add_argument('--ssj500k-frequencies',
+                        help='Tag for separators, usually pc or c', default=None)
+
     args = arg_parser.parse_args()
     logging.basicConfig(stream=sys.stderr, level=args.verbose.upper())
 

scripts/form_csv.py

@@ -0,0 +1,68 @@
+import argparse
+import csv
+import os
+
+from lxml import etree
+
+
+def write_general_statistics(path, out_list):
+    if len(out_list) == 0:
+        return
+    with open(path, 'w') as csvfile:
+        writer = csv.writer(csvfile, delimiter='\t',
+                                quotechar='"')
+        writer.writerow(['semanticRole', 'valency_pattern_ratio', 'valency_sentence_ratio'])
+        for line in out_list:
+            writer.writerow(line)
+
+
+def main(args):
+    for file in sorted(os.listdir(args.input)):
+        path = os.path.join(args.input, file)
+        tree = etree.parse(path)
+        gf_output = []
+        ssj_output = []
+        head = next(tree.iter('head'))
+        headword = head.find('headword').find('lemma').text
+        #for div in root.iterfind('.//div'):
+        for elem in tree.iter('statisticsContainer'):
+        # for element in tree.iterfind('statisticsContainer'):
+        # for element in tree.find('statisticsContainer'):
+            semRole = elem.find('semanticRole').text
+            gf_pattern = None
+            gf_sentence = None
+            ssj_pattern = None
+            ssj_sentence = None
+            measure = elem.find('measureList')
+            for el in measure:
+                if el.attrib['type'] == 'valency_pattern_ratio' and el.attrib['source'] == 'Gigafida 2.0':
+                    gf_pattern = el.text
+                if el.attrib['type'] == 'valency_sentence_ratio' and el.attrib['source'] == 'Gigafida 2.0':
+                    gf_sentence = el.text
+                if el.attrib['type'] == 'valency_pattern_ratio' and el.attrib['source'] == 'ssj500k 2.2':
+                    ssj_pattern = el.text
+                if el.attrib['type'] == 'valency_sentence_ratio' and el.attrib['source'] == 'ssj500k 2.2':
+                    ssj_sentence = el.text
+            if gf_pattern is not None and gf_sentence is not None:
+                gf_output.append([semRole, gf_pattern, gf_sentence])
+            if ssj_pattern is not None and ssj_sentence is not None:
+                ssj_output.append([semRole, ssj_pattern, ssj_sentence])
+
+        for elem in tree.iter('valencyPattern'):
+            valency_pattern_id = elem.attrib['id']
+            measure = None
+            for measure_el in elem.find('measure'):
+                if measure_el.attrib['source'] == 'Gigafida 2.0':
+                    measure = measure_el.text
+
+        write_general_statistics(os.path.join(args.output, headword + '_gf_stats.tsv'), gf_output)
+        write_general_statistics(os.path.join(args.output, headword + '_ssj_stats.tsv'), ssj_output)
+
+if __name__ == '__main__':
+    arg_parser = argparse.ArgumentParser(description='Export and validate collocation data from DDD database.')
+    arg_parser.add_argument('--input', type=str, help='Input directory')
+    arg_parser.add_argument('--output', type=str, help='Output directory')
+
+    args = arg_parser.parse_args()
+
+    main(args)

src/pkg/cjvt-corpusparser

@@ -1 +1 @@
-Subproject commit 01adf47b9b63b43f86bff52429792b0de2327ddd
+Subproject commit 92b3ac4ea3a73b93c25b363b5b9cb096d4d011cd