make tools more robust against glitches within the input files

cli.py

@@ -174,6 +174,7 @@ def ned(tsv, ner_result, ned_rest_endpoint, json_file=None, threshold=None):
     rids = []
     entity = ""
     entity_type = None
+    tsv['ID'] = '-'
 
     def check_entity(tag):
         nonlocal entity, entity_type, rids
@@ -195,7 +196,10 @@ def ned(tsv, ner_result, ned_rest_endpoint, json_file=None, threshold=None):
             entity = ""
             entity_type = None
 
-    for rid, row in tsv.iterrows():
+    ner_tmp = tsv.copy()
+    ner_tmp.loc[~ner_tmp['NE-TAG'].isin(['O', 'B-PER', 'B-LOC','B-ORG', 'I-PER', 'I-LOC', 'I-ORG']), 'NE-TAG'] = 'O'
+
+    for rid, row in ner_tmp.iterrows():
 
         check_entity(row['NE-TAG'])
 
@@ -205,7 +209,7 @@ def ned(tsv, ner_result, ned_rest_endpoint, json_file=None, threshold=None):
 
             entity += " " if entity != "" else ""
 
-            entity += row['TOKEN']
+            entity += str(row['TOKEN'])
 
             rids.append(rid)
 
@@ -321,12 +325,10 @@ def find_entities(tsv_file, tsv_out_file, ner_rest_endpoint, ned_rest_endpoint,
 
     out_columns = ['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'ID', 'url_id', 'left', 'right', 'top', 'bottom']
 
-    supported_ent = {'PER', 'LOC', 'ORG'}
-
     if noproxy:
         os.environ['no_proxy'] = '*'
 
-    tsv = pd.read_csv(tsv_file, sep='\t', comment='#', quoting=3)
+    tsv = pd.read_csv(tsv_file, sep='\t', comment='#', quoting=3).rename(columns={'GND-ID': 'ID'})
 
     parts = extract_doc_links(tsv_file)
 
@@ -343,8 +345,9 @@ def find_entities(tsv_file, tsv_out_file, ner_rest_endpoint, ned_rest_endpoint,
 
             tmp = tsv.copy()
             tmp['sen'] = (tmp['No.'] == 0).cumsum()
+            tmp.loc[~tmp['NE-TAG'].isin(['O', 'B-PER', 'B-LOC','B-ORG', 'I-PER', 'I-LOC', 'I-ORG']), 'NE-TAG'] = 'O'
 
-            ner_result = [[{'word': str(row.TOKEN), 'prediction': row['NE-TAG'] if len(row['NE-TAG']) == 1 or row['NE-TAG'][-3:] in supported_ent else 'O' } for _, row in sen.iterrows()]
+            ner_result = [[{'word': str(row.TOKEN), 'prediction': row['NE-TAG']} for _, row in sen.iterrows()]
                           for _, sen in tmp.groupby('sen')]
         else:
             raise RuntimeError("Either NER rest endpoint or NER-TAG information within tsv_file required.")